CN106092097A - Space operation orbit generation method, device - Google Patents

Abstract

The invention discloses a method and device for generating a space activity trajectory. The generation method includes: determining that the machine is in an offline state where geographic location information cannot be obtained; acquiring motion sensing data generated by an orientation sensor for representing changes in the space position of the machine ; According to the motion sensing data of one or more orientation sensors, generate one or more preliminary trajectories respectively, and fit the multiple preliminary trajectories to the space activity trajectory of the cost machine in the offline state. In addition, the present invention also provides an intelligent device for executing the generating method. The invention provides a method for generating a space activity track by an intelligent device in an offline state according to the motion sensing data of an orientation sensor assembled by itself. The generated track is accurate and reliable, and is applicable to various environments. The spatial activity trajectory generated according to this method can be used for offline navigation, offline addressing, construction of spatial layout, etc., thereby improving user experience.

Description

Method and device for generating space activity trajectory

technical field

The present invention relates to the technical field of navigation, and more specifically, to a method and device for generating a trajectory of space activity.

Background technique

Navigation has become an indispensable part of our daily life. Whether driving or walking, navigation provides us with timely and effective services. Navigation is a method of guiding a certain device from one point of a specified route to another point, which requires a clear and complete map or path between the two points. The most advanced navigation technology is the Global Positioning System (GPS), which has been widely used in vehicle anti-theft, personnel positioning and other fields. It first locates the target, and then navigates according to the map that has been drawn. The navigation route is a necessary condition for navigation, and it cannot be navigated for some spatial scenes that lack the support of the navigation route.

Generally, the generation of spatial trajectories in space can be accomplished by using the sensors on the instrument. For example, a method for realizing spatial trajectory tracking includes the following steps: calculating displacement, installing an accelerometer on the wearable device, using the accelerometer Measure the linear acceleration of the wearable device, report the frequency f and initial velocity; calculate the attitude, install the gyroscope on the wearable device, measure the angular velocity of the wearable device through the gyroscope, report the frequency f and the initial attitude of the wearable device; Drift correction; trajectory fitting, recording the displacement, attitude and drift correction information of each sampling, drawing and connecting these information, that is, fitting the trajectory of the device, thus realizing the trajectory tracking of the wearable device.

The above scheme uses the accelerometer to determine the displacement and the gyroscope to determine the attitude. The role of each sensor in generating the trajectory of space activities is relatively simple. Since the person is walking, the equipment equipped with the orientation sensor is also in a shaking state, and the above scheme is used to measure out The error of the space activity trajectory is relatively large, and the feasibility is not high.

Contents of the invention

In view of the above problems, the present invention proposes a method for generating space activity trajectories, which can generate space activity trajectories through self-assembled sensors even when the network is often disconnected, and this scheme integrates the data of various orientation sensors to obtain More accurate space activity trajectory supports navigation, addressing and other services.

In a first aspect, an embodiment of the present invention provides a method for generating a space activity trajectory, comprising the following steps:

Make sure that the machine is in an offline state where the geographic location information cannot be obtained;

Obtain the motion sensing data generated by the orientation sensor to represent the change of the spatial position of the machine;

One or more preliminary trajectories are respectively generated according to the motion sensing data of one or more orientation sensors, and the spatial activity trajectories of the cost machine in an offline state are fitted to the multiple preliminary trajectories.

In the off-line state, the present invention uses the motion sensing data collected by multiple orientation sensors assembled on the device to fit the spatial activity trajectory of the equipment, and the generated spatial activity trajectory is accurate and reliable, and is applicable to various environments. According to the method The generated spatial activity trajectory can be used for offline navigation, offline addressing, construction of spatial layout, etc., thereby improving user experience.

With reference to the first aspect, in an embodiment of the first aspect, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the machine as the movement sensory data. The inertial sensor is used to collect trajectory change data, so as to determine the change of the space activity trajectory of equipment movement according to the trajectory change data, and the direction sensor is used to collect trajectory direction change data, so as to determine the absolute geographical direction of the space activity trajectory. This kind of data is used as motion sensing data to provide a large amount of data support for the determination of space activity trajectories, so that the final generated space activity trajectories are accurate and reliable.

Preferably, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the machine as the movement sensing data. Generally, due to the large range of human motion during the movement of the equipment, the test data will have errors. In this implementation, various types of inertial sensors are used to compensate each other for errors, making the test data more For accuracy, the trajectory is more precise.

Preferably, the inertial sensor includes any one or more of the following:

The acceleration sensor is used to perceive the acceleration change value during the movement of the machine as a kind of track motion change data in the motion sensing data;

The gyroscope is used to perceive the angular rate change value during the movement of the machine as a kind of track motion change data in the motion sensing data.

In this implementation manner, the inertial sensor is mainly used to collect trajectory movement change data. Acceleration sensors and gyroscopes are the most commonly used MEMS (Micro Electro Mechanical Systems, micro-electromechanical systems) inertial sensors, which have been maturely used in various fields. The measured data are reliable and robust, which can generate accurate space activities for the subsequent sequence. Tracks provide reliable data.

Preferably, the direction sensor is a magnetometer, which is used to determine the absolute direction during the movement of the machine as a kind of track direction change data in the motion sensor data. The absolute geographical direction of the space activity trajectory cannot be determined after fitting the space activity trajectory of the device movement based on the inertial sensor. In this implementation, a magnetometer is added to determine the absolute direction of the space activity trajectory, so that the measured space The direction of the activity trajectory is more precise.

Based on the various implementations above, preferably, the motion sensor data includes at least two types of change data acquired by different orientation sensors, and there is an algorithmic correlation between the space activity trajectory and the change data. The trajectory of space activity is obtained by processing two kinds of changing data through a series of algorithms. These algorithm correlations include any number of calculus algorithms, coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms, so they are more reliable and accurate. .

With reference to the first aspect, the orientation sensor includes a plurality of sensors, and the plurality of sensors are mutually independent components, or an integrated component integrated together. According to the development of existing MEMS device technology, it is mature to integrate sensors with multiple functions into one component. The orientation sensor can be either an independent component or a component integrated together. The required orientation sensor is determined based on data requirements.

With reference to the first aspect, in one embodiment of the present invention, the motion sensing data is the data of multiple sampling points collected by at least one orientation sensor during the movement of the machine, and the preliminary trajectory is formed by connecting multiple sampling points formed by the data. The generation method of the preliminary trajectory follows the method of connecting points into a line. The more sampling points, the more accurate the generated preliminary trajectory.

With reference to the first aspect, specifically, the space activity trajectory is a local three-dimensional activity trajectory. Generally, commonly used navigation maps are planar maps. In the present invention, the space activity track is a three-dimensional activity track. Except the track on the plane, it also includes connection routes and hierarchical arrangements in the middle of different levels, so the space activity track is more accurate. Specifically, it is suitable for underground parking lots and underground shopping malls with poor signal.

In combination with the first aspect, a subsequent step is also included: the space activity track is cached in the local machine in an offline state, and the space activity track is uploaded to the cloud server after the machine recovers to access the external network. After the local machine generates the space activity trajectory, it is cached in the local machine, which will not occupy too much space, and the data can be uploaded to the cloud server in time. When the local machine resumes access to the external network, the space activity trajectory will be uploaded to the cloud server.

Combined with the first aspect, the posture state of the machine is fitted according to the motion sensor data, and after the machine returns to the state of accessing the external network, the state of motion and posture is uploaded to the cloud server together with the space activity track, so that The state of walking posture includes any one of walking, running, riding a car, standing upright and lying down. In this implementation, the posture state of the machine can also be fitted according to the motion sensor data, such as walking, running, riding, standing upright, lying down, etc. After determining the posture state of the machine, you can obtain the The human motion of the device can be applied to detect the fall of the elderly and children, and the detection of children struggling.

In combination with the first aspect, the space activity trajectory is stored as a specification file after being uploaded to the cloud server, so as to determine a target navigation route based on a plurality of specification files, and the target navigation route includes the route with the highest frequency, the shortest time route, Historical custom route. In order to apply space activity trajectories, it is stored in a standardized format to determine the target navigation route from a large inventory of space activity trajectories, and the target navigation route determined by using a large amount of data is more accurate.

In the second aspect, an embodiment of the present invention provides a device for generating a trajectory of space activities, and the generating device has the function of realizing the behavior of generating a trajectory of space activities in the above first aspect. The functions described above may be implemented by hardware, or may be implemented by executing corresponding software on the hardware. The hardware or software includes one or more modules corresponding to the above functions. The space activity trajectory generation device includes:

An offline determining unit, configured to determine that the machine is in an offline state where the geographic location information cannot be obtained;

The data acquisition unit is used to acquire the motion sensing data generated by the orientation sensor and used to represent the change of the spatial position of the machine;

The trajectory fitting unit is configured to respectively generate one or more preliminary trajectories according to the motion sensing data of one or more orientation sensors, and fit the plurality of preliminary trajectories to the space activity trajectory of the host machine in an offline state.

In conjunction with the second aspect, in an embodiment of the second aspect, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the machine as the movement sensory data.

With reference to the second aspect, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the machine as the movement sensing data.

With reference to the second aspect, in an embodiment of the second aspect, the inertial sensor includes any one or more of the following:

The acceleration sensor is used to perceive the acceleration change value during the movement of the machine as a kind of track motion change data in the motion sensing data;

The gyroscope is used to perceive the angular rate change value during the movement of the machine as a kind of track motion change data in the motion sensing data.

With reference to the second aspect, the direction sensor is preferably a magnetometer, which is used to determine the absolute direction during the movement of the machine as a kind of track direction change data in the motion sensor data.

Based on the various implementations above, the motion sensing data includes at least two types of change data acquired by different orientation sensors, and there is an algorithmic correlation between the space activity track and the change data. The algorithm correlation includes any number of calculus algorithms, coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms.

With reference to the second aspect, preferably, the orientation sensor includes a plurality of sensors, and the plurality of sensors are mutually independent components, or an integrated component integrated together.

With reference to the second aspect, specifically, the motion sensing data is the data of multiple sampling points collected by at least one orientation sensor during the movement of the machine, and the preliminary trajectory is formed by connecting the data of the multiple sampling points.

With reference to the second aspect, specifically, the space activity trajectory is a local three-dimensional activity trajectory.

With reference to the second aspect, specifically, the space activity track generation device further includes an upload unit, configured to cache the space activity track in the local machine when the space activity track is offline, and upload the space activity track when the machine is restored to the external network. The space activity track mentioned above is sent to the cloud server.

In combination with the second aspect, preferably, the posture state of the machine is fitted according to the motion sensor data, and after the machine returns to the state of accessing the external network, the state of motion and posture is uploaded together with the space activity trajectory to Cloud server, the walking posture state includes any one of walking, running, riding, standing upright and lying down.

In conjunction with the second aspect, the space activity trajectory is stored as a specification file after being uploaded to the cloud server, so as to determine the target navigation route based on multiple specification files. Preferably, the target navigation route includes the route with the highest frequency, The shortest route in time, the historical habit route.

With reference to the second aspect, in a possible design, the structure of the space activity trajectory generation device includes a processor and a memory, the memory is used to store a program that supports the transceiver device to execute the above method, and the processor is configured to A program stored in the memory is executed. The space activity track generation device may also include a communication interface for communicating with other devices or a communication network.

In a third aspect, another method for generating a space activity trajectory is provided in an embodiment of the present invention, comprising the following steps:

After the device fits the motion sensing data sensed by the orientation sensor and used to characterize the space activity trajectory into the space activity trajectory, receiving the space activity trajectory output by the device;

Storing the space activity track into a specification file.

With reference to the third aspect, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the device as the movement sensing data.

With reference to the third aspect, specifically, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the device as the movement sensing data.

With reference to the third aspect, specifically, the inertial sensor includes any one or more of the following:

The acceleration sensor is used to perceive the acceleration change value during the movement of the device as a kind of track motion change data in the motion sensing data;

The gyroscope is used to sense the change value of the angular rate during the movement of the device as a kind of track movement change data in the motion sensing data.

With reference to the third aspect, specifically, the direction sensor is a magnetometer, which is used to determine the absolute direction during the movement of the device as a kind of track direction change data in the motion sensor data.

In conjunction with the third aspect, preferably, the motion sensing data includes at least two types of change data acquired by different orientation sensors, and there is an algorithm correlation between the space activity track and the change data, and the algorithm correlation Including any number of calculus algorithms, coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms.

With reference to the third aspect, specifically, the orientation sensor includes a plurality of sensors, and the plurality of sensors are mutually independent components, or are an integrated component integrated together.

With reference to the third aspect, specifically, the motion sensing data is the data of multiple sampling points collected by at least one sensor during the movement of the device, and the preliminary trajectory is formed by connecting the data of the multiple sampling points.

In combination with the third aspect, while the device fits the motion sensing data sensed by the orientation sensor to represent the space activity trajectory into the space activity trajectory, it also fits the corresponding walking posture state according to the motion sensing data, to be completed After the space activity track and the walking posture state are generated, the space activity track and the walking posture state of the device are received, and the walking posture state includes any one of walking, running, riding, standing upright, and lying down.

With reference to the third aspect, specifically, the space activity trajectory is a three-dimensional activity trajectory.

In conjunction with the third aspect, after the space activity track is generated, it is formatted and stored as a specification file, so as to determine the target navigation route based on multiple specification files, and the target navigation route includes the route with the highest frequency, the shortest time route, and historical habits. route.

In a fourth aspect, an embodiment of the present invention provides a device for generating a space activity trajectory, and the generation device has the function of realizing the behavior of generating a space activity trajectory in the above third aspect. The functions described above may be implemented by hardware, or may be implemented by executing corresponding software on the hardware. The hardware or software includes one or more modules corresponding to the above functions, specifically including:

The trajectory receiving unit is configured to receive the spatial activity trajectory output by the device after the device fits the motion sensing data sensed by the orientation sensor and used to characterize the spatial activity trajectory into the spatial activity trajectory;

The track storage unit is used to store the track of the space activity into a specification file.

With reference to the fourth aspect, specifically, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the device as the movement sensing data.

With reference to the fourth aspect, specifically, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the device as the movement sensing data.

With reference to the fourth aspect, the inertial sensor includes any one or more of the following:

The acceleration sensor is used to perceive the acceleration change value during the movement of the device as a kind of track motion change data in the motion sensing data;

The gyroscope is used to sense the change value of the angular rate during the movement of the device as a kind of track movement change data in the motion sensing data.

With reference to the fourth aspect, specifically, the direction sensor is a magnetometer, which is used to determine the absolute direction during the movement of the device as a kind of track direction change data in the motion sensor data.

With reference to the fourth aspect, specifically, the motion sensing data includes at least two types of change data obtained by different orientation sensors, and there is an algorithmic correlation between the space activity trajectory and the change data, and the algorithmic correlation includes Any number of calculus algorithms, coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms.

With reference to the fourth aspect, the orientation sensor includes a plurality of sensors, and the plurality of sensors are mutually independent components, or an integrated component integrated together.

With reference to the fourth aspect, the motion sensing data is the data of multiple sampling points collected by at least one sensor during the movement of the device, and the preliminary trajectory is formed by connecting the data of multiple sampling points.

In combination with the fourth aspect, when the device fits the motion sensing data sensed by the orientation sensor to represent the space activity trajectory into the space activity trajectory, it also fits the corresponding walking posture state according to the motion sensing data. After the spatial activity track and the walking posture state are generated, the spatial activity trajectory and the walking posture state of the device are received, and the walking posture state includes any one of walking, running, riding, standing upright, and lying down.

With reference to the fourth aspect, the space activity trajectory is a three-dimensional activity trajectory.

In conjunction with the fourth aspect, after the space activity trajectory is generated, it is formatted and stored as a specification file, so as to determine the target navigation route based on multiple specification files, and the target navigation route includes the route with the highest frequency, the shortest time route, and historical habits. route.

With reference to the fourth aspect, in a possible design, the structure of the space activity trajectory generation device includes a processor and a memory, the memory is used to store a program that supports the transceiver device to execute the above method, and the processor is configured to A program stored in the memory is executed. The space activity track generation device may also include a communication interface for communicating with other devices or a communication network.

In a fifth aspect, the present invention provides a wearable smart device, comprising:

The touch-sensitive display is used to perceive the operation instruction and display the corresponding interface according to the instruction;

The memory is used to store programs that support the sending and receiving device to execute the above-mentioned space activity trajectory generation device;

one or more processors for executing programs stored in said memory;

A communication interface, used for the above-mentioned space activity trajectory generation device to communicate with other equipment or communication networks;

One or more application programs, the one or more programs are configured to implement the functions of the above-mentioned space activity trajectory generation device.

In a possible design, the structure of the space activity track generation device includes a processor and a memory, the memory is used to store a program that supports the transceiver device to execute the above method, and the processor is configured to execute the memory in the memory. stored program. The space activity track generation device may also include a communication interface for communicating with other devices or a communication network.

In a sixth aspect, an embodiment of the present invention provides a computer storage medium for storing computer software instructions used by the above-mentioned space activity trajectory generation device, which includes a program designed for executing the above aspect for the space activity generation device.

In the off-line state, the present invention uses the motion sensing data collected by multiple orientation sensors assembled on the device to fit the spatial activity trajectory of the equipment, and the generated spatial activity trajectory is accurate and reliable, and is applicable to various environments. According to the method The generated spatial activity trajectory can be used for offline navigation, offline addressing, construction of spatial layout, etc., thereby improving user experience. Compared with the prior art, the solution provided by the present invention allows users to use terminal devices, wearable devices, etc. to generate their own spatial activity trajectories in an offline state, and the spatial activity trajectories have high accuracy and are not limited by scenarios.

These or other aspects of the present invention will be more clearly understood in the description of the following embodiments.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings that need to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, other drawings can also be obtained based on these drawings without any creative effort.

Fig. 1 shows a system architecture diagram of a method for generating space activity trajectories according to an embodiment of the present invention.

Fig. 2 shows a structural block diagram of a device for generating space activity trajectories according to an embodiment of the present invention.

Fig. 3 shows a flow chart of a method for generating a space activity trajectory according to an embodiment of the present invention.

Fig. 4 shows a block diagram of a space activity tracking device according to an embodiment of the present invention.

Fig. 5 shows a flowchart of a method for generating a space activity trajectory according to an embodiment of the present invention.

Fig. 6 shows a block diagram of a space activity tracking device according to an embodiment of the present invention.

Fig. 7 shows a block diagram of a smart device according to an embodiment of the present invention.

detailed description

In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention.

In some processes described in the specification and claims of the present invention and the above-mentioned drawings, a plurality of operations appearing in a specific order are contained, but it should be clearly understood that these operations may not be performed in the order in which they appear herein Execution or parallel execution, the serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution order. Additionally, these processes can include more or fewer operations, and these operations can be performed sequentially or in parallel. It should be noted that the descriptions of "first" and "second" in this article are used to distinguish different messages, devices, modules, etc. are different types.

The inventor of the present invention noticed that GPS cannot provide effective navigation services for the terminal when the terminal is offline, but the demand for navigation is stronger in some places without signal, such as underground garages, railway stations and other places. The inventor noticed that the movement track of the terminal can be calculated according to the orientation sensor equipped on the terminal itself, and then the movement track can be uploaded to the cloud to provide navigation routes for places with poor signal.

The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

For the proper nouns used in the present invention are explained as follows:

Offline state. In the present invention, the device is in the offline state when it cannot receive external signals at all. Specifically, it means that it cannot receive WiFi signals, Internet signals, and GPS signals. In the offline state, the device cannot determine its own geographic location.

Space activity trajectory. In the present invention, the space activity trajectory is a three-dimensional three-dimensional trajectory of equipment movement. After determining the X-axis, Y-axis, and Z-axis of the space, the X-axis, Y-axis, and Z-axis can be used to represent the space activity trajectory respectively. The absolute east-west, north-south, and up-down directions, that is to say, each point of the generated activity trajectory has data in the three directions of X-axis, Y-axis, and Z-axis.

Orientation Sensors An orientation sensor is a series of sensors used to determine the orientation of a device.

Inertial sensors, inertial sensors are sensors that detect and measure acceleration, tilt, shock, vibration, rotation and multi-degree-of-freedom motion, and are important components for solving navigation, orientation and motion carrier control.

Gyroscope, a gyroscope is a type of inertial sensor that can measure the angular velocity of a device.

An acceleration sensor, an acceleration sensor is a type of inertial sensor that can be used to measure the acceleration of a device.

Motion sensing data, in the present invention, motion sensing data refers to the data generated by the orientation sensor for fitting and generating space activity trajectory and walking posture state.

In an embodiment of the present invention, the system architecture for generating space activity tracks is shown in FIG. 1 , including a cloud server 1000 and devices equipped with orientation sensors, such as mobile phones 1001 , smart watches 1002 and other electronic products. Taking the smart watch 1002 as an example, after the cloud server 1000 establishes a communication link with the smart watch 1002, the smart watch 1002 sends the space activity trajectory fitted according to the motion sensor data to the cloud server 1000 by wireless transmission. It can be understood by those skilled in the art that the space activity track generated by fitting can be displayed on the man-machine interface; those skilled in the art can understand that the cloud server 1000 also has better data processing capabilities, and the cloud server 1000 performs data processing When processing, the positioning data of the GPS global positioning system can also be used as a reference. For example, some collected data with large deviations can be deleted by using the GPS data.

In one embodiment of the present invention, the structural block diagram of the device used to generate the space activity trajectory is shown in Figure 2, the overall structure includes a processor, an orientation sensor module, a signal receiving module, a wireless sending module, a man-machine interface, and the like. Taking the smart watch 1002 as an example, the processor determines that it is offline when the signal receiving module fails to receive the signal. At this time, it starts the orientation sensor that comes with the machine, and receives the motion transmission sent by the orientation sensor module to represent the trajectory of the space activity. Fit the sensing data to generate a preliminary trajectory. After fitting the preliminary trajectory into a space activity trajectory, when the machine resumes access to the external network, upload the space activity trajectory to the cloud server 1000 through the wireless sending module. In this embodiment, the orientation sensor is composed of an inertial sensor and a direction sensor, and the two types of sensors respectively generate trajectory movement change data and trajectory direction change data for collecting and generating space activity trajectories. With reference to the structural block diagram of Figure 2, those skilled in the art can understand that the signal receiving module includes a WiFi signal receiving module, a satellite signal receiving module, a base station signal receiving module, etc. When any module in the module and the base station signal receiving module obtains any data, it is considered that the smart watch 1002 is in an offline state, and the recovery of the machine to the state of accessing the external network means that at least from the WiFi signal receiving module, the satellite signal receiving module and the base station signal Data is received in one of the receiving modules. Those skilled in the art can understand that the space activity track stored by the cloud server 1000 can be sent back to the smart watch 1002 and can be displayed on the man-machine interface of the smart watch 1002 .

In the first aspect, the flow chart of the first method for generating space activity trajectories provided by the present invention is shown in Figure 3, including:

S101: Determine that the local machine is in an offline state where geographic location information cannot be obtained.

When the machine cannot obtain geographic location information, it is offline, that is, it cannot determine its own geographic location through external network signals, and general geographic location information is determined by network signals such as the Internet, GPS, and WiFi networks. In one embodiment of the present invention, when the machine cannot receive the Internet signal, GPS signal, or WiFi signal, it is considered to be in an offline state. Taking the smart watch 1002 as an example, as shown in the structural block diagram of FIG. In an offline state, in one embodiment of the present invention, the steps for determining that the current state is an offline state are as follows: first judge whether there is a signal in the base station signal receiving module, it takes about 2 seconds, and then judge the GPS signal receiving module if there is no feedback from the base station signal receiving module , it takes about 5s. If there is no feedback from the GPS signal receiving module to judge WiFi, it takes about 1s. If there is no feedback from the WiFi signal, it is considered that there is no network service, and it is considered to be offline at this time; Determine your own geographic location, and then activate the orientation sensor of the smart watch 1002 to record the person's spatial activity track.

S102: Acquire motion sensing data generated by the orientation sensor and used to represent a change in the spatial position of the machine.

Those skilled in the art can understand that the orientation sensor proposed in the present invention includes a plurality of sensors, preferably MEMS sensors, which can be independently formed into components or integrated together into one component, such as integrated inside the smart watch 1002 There are three sensors, an acceleration sensor, a gyroscope, and a magnetometer, and the three orientation sensors can be three independent chips or a MEMS chip designed as one.

Specifically, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the machine as the motion sensing data. The motion sensing data is composed of two types of data, including trajectory movement change data and trajectory direction change data, and the two types of data are used to determine the direction and shape of the space activity trajectory respectively. In a possible embodiment, firstly, the trajectory movement The change data calculates the space activity trajectory, and then determines the absolute direction of the space activity trajectory according to the trajectory direction change data, thereby determining the final space activity trajectory. In this embodiment, the trajectory movement change data is used to determine the approximate shape of the trajectory , including data mapped in the three directions of X-axis, Y-axis, and Z-axis. Each point on the trajectory corresponds to the coordinates on the three coordinate axes, and the trajectory direction change data is used to calibrate and determine this spatial activity. The absolute direction of the trajectory. Combining these two kinds of data as motion sensing data provides a large amount of data support for determining the trajectory of space activities, so that the final generated trajectory of space activities is accurate and reliable.

Further, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the machine as the movement sensing data. Generally, during the moving process of the equipment, due to the relatively large range of human motion, there will be errors in the tested data. In this implementation, a variety of different types of inertial sensors are used to compensate each other for errors and drift. The test data is more accurate and the trajectory is more precise.

Specifically, the inertial sensor includes any one or more of the following: an acceleration sensor, which is used to perceive the acceleration change value during the movement of the machine as a kind of track motion change data in the motion sensor data; a gyroscope , which is used to perceive the change value of the angular rate during the movement of the machine as a kind of track movement change data in the motion sensing data. In this embodiment, for example, two kinds of inertial sensors, the gyroscope and the acceleration sensor, are used. The acceleration sensor is used to measure the acceleration of the device, and the gyroscope is used to measure the angular velocity of the device. The two sensors can be used to compensate each other for errors, so that the test The data is more accurate and the trajectory is more precise. Preferably, the acceleration sensor is preferably a three-axis acceleration sensor, the gyroscope is preferably a three-axis gyroscope, and the motion sensing data of the three axes is used to support the generation of a three-dimensional space activity trajectory, so that the generated space activity trajectory is more accurate .

Further, the direction sensor is a magnetometer, which is used to determine the absolute direction during the movement of the machine as a kind of track direction change data in the motion sensor data. Those skilled in the art can understand that the magnetic induction intensity is a vector, which has the characteristics of magnitude and direction. The magnetometer can measure the magnitude of the magnetic field in a specific direction. After fitting the space activity trajectory with the motion sensing data of the inertial sensor, the magnetometer The data corrects the absolute direction of the trajectory, so that it can be used in subsequent applications for navigation, addressing, etc.

Those skilled in the art can understand that the motion sensing data is generated by the orientation sensor and is used to represent the data of the space activity track, preferably, including at least two kinds of change data obtained by different orientation sensors, and the space activity track is related to the space activity track. Algorithm correlations exist between the above-mentioned change data, and the algorithm correlations include any number of calculus algorithms, coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms. Those skilled in the art can understand that the trajectory of space activity is obtained from the motion sensor data through a series of algorithms, including any number of calculus algorithms, coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms. For example, the smart watch 1002 is equipped with an acceleration sensor, and the three-axis acceleration sensor measures the acceleration of the smart watch 1002 on the three axes of x, y, and z as a _x , a _y , a _z , and the initial speed of the three axes v _x0 , v _y0 , v _z0 , then according to the calculus algorithm ds=vdt, the speed v _x , v _y , v _z of the smart watch 1002 in the three axes at time t is:

v _x ＝v _x0 +a _x t

v _y =v _y0 +a _y t

v _z ＝v _z0 +a _z t

Then, according to It can be concluded that the displacements of the smart watch 1002 on the three axes at time t are s _x , s _y , and s _z as follows:

s _x ＝v _x0 t+1/2a _x t ²

s _y =v _y0 t+1/2a _y t ²

s _z ＝v _z0 t+1/2a _z t ²

According to the calculus algorithm above, the acceleration, velocity and displacement corresponding to the three axes are obtained. Those skilled in the art can understand that the displacement and general direction of each point can be obtained according to these data, and then the shape of the space activity trajectory can be determined. feature. However, the completion of a space activity trajectory also requires trajectory direction change data. There is an algorithmic relationship between the space activity trajectory and the two kinds of change data of the motion sensor data. The absolute geographical direction can be detected by using the magnetometer as the trajectory direction change data for determining the space activity trajectory, and a complete space activity trajectory can be generated by combining these two kinds of change data.

Since the acceleration sensor is not on a stable platform during the actual movement of the smart watch 1002, the accurate spatial activity trajectory cannot be obtained by the calculus algorithm alone. Multiple algorithms can be used to calculate the spatial activity trajectory without affecting the accuracy. In the case of low temperature, you can also refer to external data such as GPS to obtain accurate space activity trajectories.

S103: Generate one or more preliminary trajectories respectively according to the motion sensing data of one or more orientation sensors, and fit the multiple preliminary trajectories to the space activity trajectory of the local machine when it is in an offline state.

The motion sensing data is the data of multiple sampling points collected by at least one orientation sensor during the movement of the machine, and the preliminary trajectory is formed by connecting the data of multiple sampling points. The generation method of the preliminary trajectory follows the method of connecting points into a line. The more sampling points, the more accurate the generated preliminary trajectory. In this embodiment, the method of generating the preliminary trajectory is to connect the motion sensor data of multiple sampling points into a line, and the motion sensor data to generate a preliminary trajectory can be the data collected by a single sensor or multiple Data collected by sensors. For example, there are two inertial sensors and one direction sensor on the smart watch 1002. The inertial sensor is a gyroscope and an acceleration sensor, and the direction sensor is a magnetometer. The first preliminary trajectory can be the data of multiple points collected by the acceleration sensor. Fitting generation; the second preliminary trajectory can be generated by the data of multiple points collected by the gyroscope and the data of multiple points collected by the magnetometer; the third preliminary trajectory can be generated by data of multiple points collected by the acceleration sensor Synthetic magnetometer fit generation.

After the multiple preliminary trajectories are finally determined, the space activity trajectory can be determined according to the degree of deviation of the multiple trajectories. If a plurality of tracks are all consistent, then no further calculation is necessary. If the tracks do not match, the cloud server 1000 needs to determine which track has an error. The cloud server 1000 can determine a track according to the GPS positioning data. If a preliminary trajectory is relatively close to the GPS positioning data, the preliminary trajectory is defined as the space activity trajectory.

To judge whether the trajectories are similar, mathematical algorithms can be used, such as the algorithm for calculating the sum of squared errors, such as taking the Z-axis data corresponding to different time points on the two trajectories. If at the first second, the Z-axis data on the two trajectories are 4.6, 4.5, at the second second, the Z-axis data are 5.8, 5.8 respectively, at the third second, the Z-axis data are 3.1, 3.4 respectively, then the sum of the squares of the error is:

(4.6-4.5) ² +(5.8-5.8) ² +(3.1-3.4) ² ＝0.1

Continue to calculate the sum of squares of errors on the X-axis and Y-axis at different times according to the above algorithm. Those skilled in the art can understand that the smaller the calculated sum of squares of errors, the closer the two curves are, and the higher the matching procedure , other algorithms, for example, Frescher distance algorithm, machine learning algorithm, clustering algorithm, etc. can also be applied to detect trajectory similarity, and the present invention does not limit the algorithm used, as long as it can determine the similarity between trajectories. Can.

Those skilled in the art can understand that since the orientation sensors used are all preferably three-axis sensors, data on three axes can be obtained, so it is not difficult to understand that the space activity trajectory is the three-dimensional activity trajectory of the machine. Compared with the two-dimensional planar trajectory, the three-dimensional activity trajectory has a better applicable space, and meets the navigation needs of places with complex structures, such as railway stations, underground multi-storey parking lots, and large shopping malls. For example, according to the method provided by the present invention, the distribution signs such as the structure of each floor of the shopping mall, the stairs between the floors, and the elevators can be reflected.

In an embodiment of the present invention, a subsequent step is also included: the space activity trajectory is cached in the local machine in an offline state, and the space activity trajectory is uploaded to the cloud server after the local machine recovers to access the external network. Before this, the space activity track is cached in the local machine in a cache mode, which will not occupy the device space and ensure that the data will not be lost.

In one embodiment of the present invention, the posture state of the machine is fitted according to the motion sensing data. The motion sensing data can not only be used to determine the space activity trajectory, but also can be used to fit the posture state. The smart watch 1002 For example, after the machine returns to the state of accessing the external network, upload the walking posture state together with the space activity trajectory to the cloud server, and the walking posture state includes walking, running, riding, standing upright, lying down item. For the smart watch 1002, when it is equipped with an acceleration sensor, the body of the smart watch 1002 measures the acceleration of front and rear, up and down, and left and right. When wearing the smart watch 1002, when people walk, the front and rear acceleration measured by the acceleration sensor is relatively large, the up and down acceleration is small, and the acceleration value changes periodically in a certain direction. Those skilled in the art can understand that it can be judged that a person is walking according to such data; It is small, but the acceleration in the up and down direction is relatively large. The swing arm seems to be in a circle. The collected data is also a periodic value. According to the characteristics of the acceleration data and the characteristics of the sampling period, it can also be judged that the person is running. While fitting the spatial activity trajectory, it can also detect the state information of the person's walking posture, which can be widely used in the detection of the fall of the elderly and the detection of the loss of a child. Those skilled in the art can understand that after the child is lost, it can Judging the child's condition based on the posture status information, whether the child is struggling, whether the child is standing still, etc.

After the cloud server 1000 receives the motion sensing data, it fits and generates the space activity trajectory, and the multiple space activity trajectories marked as the same place can be stored in the memory in a standardized format, that is, the space activity trajectory is stored as a specification file , to determine the target navigation route based on multiple specification files. Valuable information can be quickly obtained from a large amount of data, such as the target navigation route described in the present invention, such as the route with the highest frequency, the route with the shortest time, and the route of historical habit. Taking the smart watch 1002 as an example, the route with the highest frequency is the route that is traveled the most in the same space; the shortest time route refers to the route with the shortest time between a fixed starting point and a fixed end point; the historical habit route refers to the route corresponding to the smart watch 1002 The habitual route of identity information, those skilled in the art can understand, when someone A wearing the smart watch 1002 walks in the place A, record the motion sensor data and upload it to the cloud server 1000, and the cloud server 1000 recognizes A's identity Afterwards, the space activity trajectory C is generated and stored in the cloud memory. When A arrives at the place A again, he wants to find the navigation route, so A sends a request to the cloud server 1000, and the cloud server 1000 identifies the identity of A and provides information about where A has traveled. The past spatial activity trajectory C is used as a historical habit route, and other types of routes generated from multiple routes are provided at the same time.

In the second aspect, an embodiment of the present invention provides a device for generating a trajectory of space activities, and the generating device has the function of realizing the behavior of generating a trajectory of space activities in the above first aspect. The functions described above may be implemented by hardware, or may be implemented by executing corresponding software on the hardware. The hardware or software includes one or more modules corresponding to the above functions, as shown in Figure 4, including:

An offline determining unit, configured to determine that the machine is in an offline state where the geographic location information cannot be obtained;

The data acquisition unit is used to acquire the motion sensing data generated by the orientation sensor and used to represent the change of the spatial position of the machine;

The trajectory fitting unit is configured to respectively generate one or more preliminary trajectories according to the motion sensing data of one or more orientation sensors, and fit the plurality of preliminary trajectories to the space activity trajectory of the host machine in an offline state.

Specifically, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the machine as the movement sensing data.

Specifically, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the machine as the movement sensing data.

The inertial sensor includes any one or more of the following:

The acceleration sensor is used to perceive the acceleration change value during the movement of the machine as a kind of track motion change data in the motion sensing data;

The gyroscope is used to perceive the angular rate change value during the movement of the machine as a kind of track motion change data in the motion sensing data.

Specifically, the direction sensor is a magnetometer, which is used to determine the absolute direction during the movement of the machine as a kind of track direction change data in the motion sensor data.

Preferably, the motion sensing data includes at least two kinds of change data acquired by different orientation sensors, and there is an algorithm correlation between the space activity track and the change data, and the algorithm correlation includes calculus algorithm, Any number of coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms.

Further, the orientation sensor includes a plurality of sensors, and the plurality of sensors are mutually independent components, or an integrated component integrated together.

Specifically, the motion sensing data is the data of multiple sampling points collected by at least one orientation sensor during the movement of the machine, and the preliminary track is formed by connecting the data of multiple sampling points.

Preferably, the space activity trajectory is a three-dimensional activity trajectory of the machine.

Preferably, it also includes an uploading unit, wherein the space activity track is cached in the local machine in an offline state, and uploads the space activity track to the cloud server after the machine recovers to access the external network.

Further, the walking posture state of the machine is fitted according to the motion sensor data, and after the machine returns to the state of accessing the external network, the walking posture state is uploaded to the cloud server together with the space activity trajectory, and the walking posture The state includes any one of walking, running, riding, standing upright and lying down.

Preferably, the space activity trajectory is stored as a specification file after being uploaded to the cloud server, so as to determine a target navigation route based on a plurality of specification files, and the target navigation route includes the route with the highest frequency, the shortest time route, the history Get used to the route.

In a third aspect, the present invention also provides another method for generating space activity trajectories, as shown in Figure 5, including:

After the device fits the motion sensing data sensed by the orientation sensor and used to characterize the space activity trajectory into the space activity trajectory, receiving the space activity trajectory output by the device;

Storing the space activity trajectory into a specification file.

Specifically, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the device as the movement sensing data.

Specifically, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the device as the movement sensing data.

Specifically, the inertial sensor includes any one or more of the following:

The acceleration sensor is used to perceive the acceleration change value during the movement of the device as a kind of track motion change data in the motion sensing data;

The gyroscope is used to sense the change value of the angular rate during the movement of the device as a kind of track movement change data in the motion sensing data.

Further, the direction sensor is a magnetometer, which is used to determine the absolute direction during the movement of the device as a kind of track direction change data in the motion sensor data.

Further, the motion sensing data includes at least two kinds of change data acquired by different orientation sensors, and there is an algorithm correlation between the space activity track and the change data, and the algorithm correlation includes calculus algorithm, coordinate transformation Any number of algorithms, pattern recognition algorithms, and data fusion algorithms.

Further, the orientation sensor includes a plurality of sensors, and the plurality of sensors are mutually independent components, or an integrated component integrated together.

Specifically, the motion sensing data is the data of multiple sampling points collected by at least one sensor during the movement of the device, and the preliminary trajectory is formed by connecting the data of the multiple sampling points.

Specifically, while the device is fitting the motion sensing data sensed by the orientation sensor to represent the spatial activity trajectory into the spatial activity trajectory, the corresponding walking posture state is fitted according to the motion sensing data, and the generation of space After the activity track and walking posture state, the space activity track and walking posture state of the device are received, and the walking posture state includes any one of walking, running, riding, standing upright, and lying down.

Preferably, the space activity trajectory is a three-dimensional activity trajectory.

Further, after the space activity trajectory is generated, it is formatted and stored as a specification file, so as to determine the target navigation route based on multiple specification files.

Specifically, the target navigation route includes a route with the highest frequency, a route with the shortest time, and a historical habit route.

In a fourth aspect, an embodiment of the present invention provides another device for generating a space activity trajectory, which has the function of realizing the behavior of generating a space activity trajectory in the above third aspect. The functions described above may be implemented by hardware, or may be implemented by executing corresponding software on the hardware. The hardware or software includes one or more modules corresponding to the above functions, as shown in Figure 6, including:

The trajectory receiving unit 201 is configured to receive the spatial activity trajectory output by the device after the device fits the motion sensing data sensed by the orientation sensor and used to characterize the spatial activity trajectory into the spatial activity trajectory;

The track storage unit 202 is configured to store the space activity track into a specification file.

Further, in one embodiment of the present invention, the orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect trajectory movement change data and trajectory direction change data during the movement of the device as the motion sensing data.

Further, the orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the device as the movement sensing data.

Specifically, the inertial sensor includes any one or more of the following:

The acceleration sensor is used to perceive the acceleration change value during the movement of the device as a kind of track motion change data in the motion sensing data;

The gyroscope is used to sense the change value of the angular rate during the movement of the device as a kind of track movement change data in the motion sensing data.

Specifically, the direction sensor is a magnetometer, which is used to determine the absolute direction during the movement of the device as a kind of track direction change data in the motion sensor data.

Specifically, the motion sensing data includes at least two types of change data acquired by different orientation sensors, and there is an algorithmic correlation between the space activity trajectory and the change data.

The algorithm correlation includes any number of calculus algorithms, coordinate transformation algorithms, pattern recognition algorithms, and data fusion algorithms.

Specifically, the orientation sensor includes a plurality of sensors, and the plurality of sensors are mutually independent components, or an integrated component integrated together.

Specifically, the motion sensing data is the data of multiple sampling points collected by at least one sensor during the movement of the device, and the preliminary trajectory is formed by connecting the data of the multiple sampling points.

Further, in combination with the fourth aspect, when the device fits the motion sensing data sensed by the orientation sensor and used to characterize the space activity trajectory into the space activity trajectory, it also fits the corresponding walking posture state according to the motion sensing data, After the spatial activity trajectory and the walking posture state are generated, the spatial activity trajectory and the walking posture state of the device are received.

Further, the walking posture state includes any one of walking, running, riding, standing upright, and lying down.

Preferably, the space activity trajectory is a three-dimensional activity trajectory of the device.

Specifically, the target navigation route includes a route with the highest frequency, a route with the shortest time, and a historical habit route.

In the fifth aspect, the embodiment of the present invention also provides a smart device, and the embodiment of the present invention also provides a smart device, including:

The touch-sensitive display is used to perceive the operation instruction and display the corresponding interface according to the instruction;

The memory is used to store programs that support the sending and receiving device to execute the above-mentioned space activity trajectory generation device;

one or more processors for executing programs stored in said memory;

A communication interface, used for the above-mentioned space activity trajectory generation device to communicate with other equipment or communication networks;

One or more application programs, the one or more programs configured to implement the functions of any one of the space activity trajectory generation devices described above.

The smart device described in the present invention refers to a smart device equipped with an orientation sensor. As shown in Figure 7, for the sake of illustration, only the parts related to the embodiment of the present invention are shown. For specific technical details not disclosed, please refer to this Invention Examples Methods Section. The smart device can be smart watch 1002, smart bracelet, mobile phone 1001, PDA (Personal Digital Assistant, personal digital assistant), POS (Point of Sales, sales terminal), vehicle-mounted computer, etc. The smart device described in the present invention is equipped with The smart device of the orientation sensor, taking the smart watch 1002 as an example:

Fig. 7 shows a block diagram of a partial structure of a smart watch 1002 related to the smart device provided by the embodiment of the present invention. Referring to FIG. 7 , the smart watch 1002 includes: a touch-sensitive display 701, a memory 702, a communication interface 703, one or more processors 704, one or more application programs 705, a power supply 706, a WiFi receiving module 707 and other components. Those skilled in the art can understand that the structure of the smart watch 1002 shown in FIG. 7 does not constitute a limitation to the smart watch 1002, and may include more or less components than those shown in the illustration, or combine certain components, or different components. layout.

The components of the smart watch 1002 are specifically introduced below in conjunction with FIG. 7 :

The touch-sensitive display 701 is a combination of a touch screen and a display screen, each of which occupies one layer; the touch screen includes a touch panel, which can collect touch operations of the user on or near it (for example, the user uses a finger, a stylus, etc.) Any suitable object or accessory is operated on or near the touch panel), and the corresponding connected device is driven according to a preset program. Optionally, the touch panel may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, and detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into contact coordinates, and sends it to the to the processor 704, and can receive and execute commands sent by the processor 704. In addition, various types of touch panels, such as resistive, capacitive, infrared, and surface acoustic wave, can be used to realize the touch panel. In addition to the touch panel, a display screen may be used to display information input by or provided to the user and various menus of the smart watch 1002 . The display screen includes a display panel. Optionally, the display panel may be configured in the form of a liquid crystal display (Liquid Crystal Display, LCD), an organic light-emitting diode (Organic Light-Emitting Diode, OLED), or the like. Further, the touch panel can cover the display panel, and when the touch panel detects a touch operation on or near it, it will be sent to the processor 704 to determine the type of the touch event, and then the processor 704 will display on the display according to the type of the touch event. The corresponding visual output is provided on the panel. Although in FIG. 7, the touch panel and the display panel are used as two independent components to realize the input and input functions of the smart watch 1002, but in some embodiments, the touch panel and the display panel can be integrated to realize smart watch 1002. Input and output functions of watch 1002.

The memory 702 can be used to store software programs and modules, and the processor 704 executes various functional applications and data processing of the smart watch 1002 by running the software programs and modules stored in the memory 702 . The memory 702 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one function required application program 705 (such as a sound playback function, an image playback function, etc.) etc.; the storage data area can store Data created according to the use of the smart watch 1002 (such as audio data, phone book, etc.) and the like. In addition, the memory 702 may include a high-speed random access storage area 702, and may also include a non-volatile storage area 702, such as at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

The communication interface 703 is used for the above-mentioned space activity trajectory generation device to communicate with other devices or communication networks. The communication interface 703 is an interface for the processor 704 to communicate with other devices, and is used for information transmission between the processor 704 and other devices, and the communication interface is also the main medium for the processor to communicate with the cloud server 1000 .

The processor 704 is the control center of the smart watch 1002. It uses various communication interfaces 703 and lines to connect the various parts of the whole smart watch 1002. By running or executing the software programs and/or modules stored in the storage area 702, and calling the stored in the The data in the storage area 702 executes various functions of the smart watch 1002 and processes data, so as to monitor the smart watch 1002 as a whole. Optionally, the processor 704 may include one or more processing units; preferably, the processor 704 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface and application program 705 etc., the modem processor mainly handles wireless communication. It can be understood that the foregoing modem processor may not be integrated into the processor 704 .

One or more application programs 705, preferably, these application programs 705 are all stored in the storage area 702 and configured to be executed by the one or more processors 704, the one or more application programs 705 Any embodiment configured to perform the method for generating a trajectory of space activity.

The smart watch 1002 also includes a power supply 706 (such as a battery) for supplying power to various components. Preferably, the power supply 706 can be logically connected to the processor 704 through the power management system, so as to manage charging, discharging, and power consumption through the power management system 706. and other functions.

WiFi is a short-distance wireless transmission technology. The mobile phone can help users send and receive emails, browse web pages, and access streaming media through the WiFi module 707. It provides users with wireless broadband Internet access.

Although not shown, the smart watch 1002 may also include a camera, a Bluetooth module, etc., which will not be repeated here.

In the embodiment of the present invention, the processor 704 included in the smart device also has the following functions:

Make sure that the machine is in an offline state where the geographic location information cannot be obtained;

Obtain the motion sensing data generated by the orientation sensor to represent the change of the spatial position of the machine;

One or more preliminary trajectories are respectively generated according to the motion sensing data of one or more orientation sensors, and the spatial activity trajectories of the cost machine in an offline state are fitted to the multiple preliminary trajectories.

An embodiment of the present invention also provides a computer storage medium for storing computer software instructions used by the above-mentioned space activity trajectory generation device, which includes instructions for executing the above-mentioned second aspect and the fourth aspect for the space activity trajectory generation device designed program.

Those skilled in the art can clearly understand that for the convenience and brevity of the description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiment, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or May be integrated into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

Those of ordinary skill in the art can understand that all or part of the steps in the various methods of the above-mentioned embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: Read Only Memory (ROM, Read Only Memory), Random Access Memory (RAM, Random Access Memory), magnetic disk or optical disk, etc.

A smart device provided by the present invention has been introduced in detail above. For those of ordinary skill in the art, according to the idea of the embodiment of the present invention, there will be changes in the specific implementation and application range. In summary , the contents of this specification should not be construed as limiting the present invention.

Claims (10)

1. A method for generating a space activity trajectory, comprising: Make sure that the machine is in an offline state where the geographic location information cannot be obtained; Obtain the motion sensing data generated by the orientation sensor to represent the change of the spatial position of the machine; One or more preliminary trajectories are respectively generated according to the motion sensing data of one or more orientation sensors, and the spatial activity trajectories of the cost machine in an offline state are fitted to the multiple preliminary trajectories. 2. The generation method according to claim 1, characterized in that, The orientation sensor includes an inertial sensor and a direction sensor, which are respectively used to collect track motion change data and track direction change data during the movement of the machine as the motion sensing data. 3. The generation method according to claim 2, characterized in that, The orientation sensor includes a plurality of different types of inertial sensors, all of which are used to collect trajectory movement change data during the movement of the machine as the movement sensing data. 4. A space activity track generation device, characterized in that, comprising: An offline determining unit, configured to determine that the machine is in an offline state where the geographic location information cannot be obtained; The data acquisition unit is used to acquire the motion sensing data generated by the orientation sensor and used to represent the change of the spatial position of the machine; The trajectory fitting unit is configured to respectively generate one or more preliminary trajectories according to the motion sensing data of one or more orientation sensors, and fit the plurality of preliminary trajectories to the space activity trajectory of the host machine in an offline state. 5 . The generating device according to claim 4 , wherein the space activity trajectory is a local three-dimensional activity trajectory. 6 . 6. A method for generating a space activity trajectory, comprising: After the device fits the motion sensing data sensed by the orientation sensor and used to characterize the space activity trajectory into the space activity trajectory, receiving the space activity trajectory output by the device; Storing the space activity trajectory into a specification file. 7. The generation method according to claim 6, wherein the orientation sensor comprises an inertial sensor and a direction sensor, which are used to collect trajectory movement change data and trajectory direction change data during the movement of the device as the motion sensor data. 8. The generation method according to claim 6, wherein the orientation sensor comprises a plurality of sensors, and the plurality of sensors are mutually independent components, or are an integrated component integrated together. 9. A space activity track generation device, characterized in that, comprising: The trajectory receiving unit is configured to receive the spatial activity trajectory output by the device after the device fits the motion sensing data sensed by the orientation sensor and used to characterize the spatial activity trajectory into the spatial activity trajectory; The track storage unit is used to store the track of the space activity into a specification file. 10. A wearable smart device, characterized in that, comprising: The touch-sensitive display is used to perceive the operation instruction and display the corresponding interface according to the instruction; The memory is used to store programs that support the sending and receiving device to execute the above-mentioned space activity trajectory generation device; one or more processors for executing programs stored in said memory; A communication interface, used for the above-mentioned space activity trajectory generation device to communicate with other equipment or communication networks; One or more application programs, the one or more programs configured to implement the functions of the device for generating space activity trajectories according to any one of claims 4 and 9 above.