In this paper we examine the submerged rigid body as motivation for the exten-sion of the notion ... more In this paper we examine the submerged rigid body as motivation for the exten-sion of the notion of decoupling vector fields to include motion in a viscous fluid. We give a relationship between decoupling vector fields and the singular extremals for the system which links the optimization of the motion planning problem to the inherent geometric framework. We end by showing how this connection is ap-plied to the creation of time efficient trajectories which are implementable onto a test-bed autonomous underwater vehicle (AUV).
This paper discusses control strategies adapted for practical imple-mentation on underwater vehic... more This paper discusses control strategies adapted for practical imple-mentation on underwater vehicles. The goal is to design trajectories cor-responding to a piecewise constant thrust with a small number of switch-ings. Moreover, we want our trajectories to be time efficient. We provide an algorithm based on optimization techniques for the time minimal prob-lem.
ABSTRACT Establishing a persistent presence in the ocean with an autonomous underwater vehicle (A... more ABSTRACT Establishing a persistent presence in the ocean with an autonomous underwater vehicle (AUV) capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of vehicles that can only control their depth in the water column for such extended deployments. We present a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy and enables general control for these profiling floats. The proposed method is based on experimentally validated techniques for utilizing ocean current models to control autonomous gliders. With the appropriate vertical actuation, and utilizing spatio–temporal variations in water speed and direction, we show that general controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution. A computed depth plan is generated with a model-predictive controller (MPC), and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA, USA, that show encouraging results in the ability of a drifting vehicle to reach a desired location.
... for Embedded Networked Sensing Networked Robotic Sensor Platform Deployments for use in Coast... more ... for Embedded Networked Sensing Networked Robotic Sensor Platform Deployments for use in Coastal Environmental Assessment in Southern California Arvind Pereira 1 , Jnaneshwar Das 1 , Hordur Heidarsson 1 , Ryan N. Smith 1 , Beth Stauffer 2 , Erica Seubert 2 , Marie ...
Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanog... more Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver one or many vehicles to high-valued locations to collect data with scientific merit. We consider the use of ocean model predictions to determine the locations to be visited by a team of AUVs, which then provides near-real time, in situ measurements back to the model to increase model skill and the accuracy of future predictions. Iterative application of this procedure ...
This paper discusses control strategies adapted for practical implementation and efficient motion... more This paper discusses control strategies adapted for practical implementation and efficient motion of autonomous underwater vehicles (AUVs). For AUVs we would like efficiency in both the measured time and the energy consumption, the mission dictating the weight to put on each of these cost. As a first approach to this problem, we focus in this paper on time minimization.
In this paper we consider the implementation of time and energy efficient trajectories onto a tes... more In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.
Abstract In this paper, we present a control strategy design technique for an autonomous underwat... more Abstract In this paper, we present a control strategy design technique for an autonomous underwater vehicle based on solutions to the motion planning problem derived from differential geometric methods. The motion planning problem is motivated by the practical application of surveying the hull of a ship for implications of harbor and port security. In recent years, engineers and researchers have been collaborating on automating ship hull inspections by employing autonomous vehicles.
IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles , Jul 2012
Establishing a persistent presence in the ocean with an AUV to observe temporal variability of la... more Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.
Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of ... more Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats.
With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.
Proceedings of the International Conference on Robotics and Automation, 2013
Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid... more Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Al- though these models provide information at a unprecedented resolutions and have proven to increase accuracy and effective- ness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles.
For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current veloc- ity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.
Proceedings of the IEEE International Conference on Robotics and Automation, 2013
Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles.... more Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.
Habitat structural complexity influences key ecological processess, which influence ecosystem bio... more Habitat structural complexity influences key ecological processess, which influence ecosystem biodiversity and resilience. Previous attempts to quantify complexity of underwater habitats have proven labor intensive and not very accurate; thus not practical nor useful for widespread research, management or conservation across large spatial scales. We propose a novel methodology to accurately compute structural complexity with reduced effort and without invasive techniques, using coral reefs as an example. Coral reefs are valuable ecosystems to human kind, yet they are disappearing at an alarming rate. U3D, our method, involves a set of innovative, multi-view image processing algorithms, which provide rapid and accurate three-dimensional reconstruction from footage taken with a monocular video or still camera. U3D quantifies habitat structural complexity at multiple spatial scales, e.g. from newley settled corals to entire coral reefs. Here, we demonstrate the 3D reconstruction of a coral colony (Acropora spp.) to < 1 mm accuracy over 90% of its surface area, and accurately compute structural complexity of a fore reef area of > 400 m2. The computed structural complexity is compared with empirical in situ measurements and shows that current methodologies significantly underestimate or overestimate measurements, such as surface area and volume of coral colonies. Additionally, we can utilise any existing video sequences taken from any type of underwater camera from any reef habitat or location. This provides an infinite array of possibilities for future research by producing a cost-effective and automated method of quantifying structural complexity, growth and bioerosion, from both new and historical video surveys of underwater habitats, such as coral reefs.
Proceedings of the American Control Conference, 2013
A priority when designing control strategies for autonomous underwater vehicles is to emphasize t... more A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.
In this paper we examine the submerged rigid body as motivation for the exten-sion of the notion ... more In this paper we examine the submerged rigid body as motivation for the exten-sion of the notion of decoupling vector fields to include motion in a viscous fluid. We give a relationship between decoupling vector fields and the singular extremals for the system which links the optimization of the motion planning problem to the inherent geometric framework. We end by showing how this connection is ap-plied to the creation of time efficient trajectories which are implementable onto a test-bed autonomous underwater vehicle (AUV).
This paper discusses control strategies adapted for practical imple-mentation on underwater vehic... more This paper discusses control strategies adapted for practical imple-mentation on underwater vehicles. The goal is to design trajectories cor-responding to a piecewise constant thrust with a small number of switch-ings. Moreover, we want our trajectories to be time efficient. We provide an algorithm based on optimization techniques for the time minimal prob-lem.
ABSTRACT Establishing a persistent presence in the ocean with an autonomous underwater vehicle (A... more ABSTRACT Establishing a persistent presence in the ocean with an autonomous underwater vehicle (AUV) capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of vehicles that can only control their depth in the water column for such extended deployments. We present a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy and enables general control for these profiling floats. The proposed method is based on experimentally validated techniques for utilizing ocean current models to control autonomous gliders. With the appropriate vertical actuation, and utilizing spatio–temporal variations in water speed and direction, we show that general controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution. A computed depth plan is generated with a model-predictive controller (MPC), and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA, USA, that show encouraging results in the ability of a drifting vehicle to reach a desired location.
... for Embedded Networked Sensing Networked Robotic Sensor Platform Deployments for use in Coast... more ... for Embedded Networked Sensing Networked Robotic Sensor Platform Deployments for use in Coastal Environmental Assessment in Southern California Arvind Pereira 1 , Jnaneshwar Das 1 , Hordur Heidarsson 1 , Ryan N. Smith 1 , Beth Stauffer 2 , Erica Seubert 2 , Marie ...
Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanog... more Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver one or many vehicles to high-valued locations to collect data with scientific merit. We consider the use of ocean model predictions to determine the locations to be visited by a team of AUVs, which then provides near-real time, in situ measurements back to the model to increase model skill and the accuracy of future predictions. Iterative application of this procedure ...
This paper discusses control strategies adapted for practical implementation and efficient motion... more This paper discusses control strategies adapted for practical implementation and efficient motion of autonomous underwater vehicles (AUVs). For AUVs we would like efficiency in both the measured time and the energy consumption, the mission dictating the weight to put on each of these cost. As a first approach to this problem, we focus in this paper on time minimization.
In this paper we consider the implementation of time and energy efficient trajectories onto a tes... more In this paper we consider the implementation of time and energy efficient trajectories onto a test-bed autonomous underwater vehicle. The trajectories are losely connected to the results of the application of the maximum principle to the controlled mechanical system. We use a numerical algorithm to compute efficient trajectories designed using geometric control theory to optimize a given cost function. Experimental results are shown for the time minimization problem.
Abstract In this paper, we present a control strategy design technique for an autonomous underwat... more Abstract In this paper, we present a control strategy design technique for an autonomous underwater vehicle based on solutions to the motion planning problem derived from differential geometric methods. The motion planning problem is motivated by the practical application of surveying the hull of a ship for implications of harbor and port security. In recent years, engineers and researchers have been collaborating on automating ship hull inspections by employing autonomous vehicles.
IFAC Workshop on Navigation, Guidance and Control of Underwater Vehicles , Jul 2012
Establishing a persistent presence in the ocean with an AUV to observe temporal variability of la... more Establishing a persistent presence in the ocean with an AUV to observe temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we propose a strategy that utilizes ocean model predictions to increase the autonomy and control of Lagrangian or profiling floats for precisely this purpose. An A* planner is applied to a local controllability map generated from predictions of ocean currents to compute a path between prescribed waypoints that has the highest likelihood of successful execution. The control to follow the planned path is computed by use of a model predictive controller. This controller is designed to select the best depth for the vehicle to exploit ambient currents to reach the goal waypoint. Mission constraints are employed to simulate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, and show surprising results in the ability of a Lagrangian float to reach a desired location.
Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of ... more Establishing a persistent presence in the ocean with an Autonomous Underwater Vehicle capable of observing temporal variability of large-scale ocean processes requires a unique sensor platform. In this paper, we examine the utility of Lagrangian profiling floats for such extended deployments. We propose a strategy that utilizes ocean model predictions to facilitate a basic level of autonomy to achieve general control of this minimally-actuated underwater vehicle. We extend experimentally validated techniques for utilising ocean current models to control under-actuated autonomous underwater vehicles by presenting this investigation into the application of these methods on profiling floats.
With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.
Proceedings of the International Conference on Robotics and Automation, 2013
Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid... more Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Al- though these models provide information at a unprecedented resolutions and have proven to increase accuracy and effective- ness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles.
For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current veloc- ity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.
Proceedings of the IEEE International Conference on Robotics and Automation, 2013
Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles.... more Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.
Habitat structural complexity influences key ecological processess, which influence ecosystem bio... more Habitat structural complexity influences key ecological processess, which influence ecosystem biodiversity and resilience. Previous attempts to quantify complexity of underwater habitats have proven labor intensive and not very accurate; thus not practical nor useful for widespread research, management or conservation across large spatial scales. We propose a novel methodology to accurately compute structural complexity with reduced effort and without invasive techniques, using coral reefs as an example. Coral reefs are valuable ecosystems to human kind, yet they are disappearing at an alarming rate. U3D, our method, involves a set of innovative, multi-view image processing algorithms, which provide rapid and accurate three-dimensional reconstruction from footage taken with a monocular video or still camera. U3D quantifies habitat structural complexity at multiple spatial scales, e.g. from newley settled corals to entire coral reefs. Here, we demonstrate the 3D reconstruction of a coral colony (Acropora spp.) to < 1 mm accuracy over 90% of its surface area, and accurately compute structural complexity of a fore reef area of > 400 m2. The computed structural complexity is compared with empirical in situ measurements and shows that current methodologies significantly underestimate or overestimate measurements, such as surface area and volume of coral colonies. Additionally, we can utilise any existing video sequences taken from any type of underwater camera from any reef habitat or location. This provides an infinite array of possibilities for future research by producing a cost-effective and automated method of quantifying structural complexity, growth and bioerosion, from both new and historical video surveys of underwater habitats, such as coral reefs.
Proceedings of the American Control Conference, 2013
A priority when designing control strategies for autonomous underwater vehicles is to emphasize t... more A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.
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Papers by Ryan N. Smith
With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.
For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current veloc- ity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.
With the appropriate vertical actuation, and utilising spatiotemporal variations in water speed and direction, we show that broad controllability results can be met. First, we apply an A* planner to a local controllability map generated from predictions of ocean currents. This computes a path between start and goal waypoints that has the highest likelihood of successful execution over a given duration. The computed depth plan is generated with a model predictive controller, and selects the depths for the vehicle so that ambient currents guide it toward the goal. Mission constraints are included to simulate and motivate a practical data collection mission. Results are presented in simulation for a mission off the coast of Los Angeles, CA USA, that show surprising results in the ability of a drifting vehicle to maintain a prescribed course and reach a desired location.
For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current veloc- ity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.