[go: up one dir, main page]

Mazaheri et al., 2024 - Google Patents

Path planning in three-dimensional space based on butterfly optimization algorithm

Mazaheri et al., 2024

View HTML
Document ID
7944590202045874538
Author
Mazaheri H
Goli S
Nourollah A
Publication year
Publication venue
Scientific Reports

External Links

Snippet

Path planning is one of the most critical issues in many related fields including UAVs. Many researchers have addressed this problem according to different conditions and limitations, but modelling the 3-D space and routing with an evolutional algorithm in such spaces is an …
Continue reading at www.nature.com (HTML) (other versions)

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291Fleet control
    • G05D1/0295Fleet control by at least one leading vehicle of the fleet
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0255Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/0011Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
    • G05D1/0044Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement by providing the operator with a computer generated representation of the environment of the vehicle, e.g. virtual reality, maps
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02Control of position or course in two dimensions
    • G05D1/021Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • G05D1/0278Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/004Artificial life, i.e. computers simulating life
    • G06N3/006Artificial life, i.e. computers simulating life based on simulated virtual individual or collective life forms, e.g. single "avatar", social simulations, virtual worlds
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2201/00Application
    • G05D2201/02Control of position of land vehicles
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management

Similar Documents

Publication Publication Date Title
Yahia et al. Path planning optimization in unmanned aerial vehicles using meta-heuristic algorithms: A systematic review
Salzmann et al. Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data
Yang et al. Survey of robot 3D path planning algorithms
Mazaheri et al. Path planning in three-dimensional space based on butterfly optimization algorithm
Wang et al. A parallel particle swarm optimization and enhanced sparrow search algorithm for unmanned aerial vehicle path planning
Song et al. Online coverage and inspection planning for 3D modeling
Ge et al. Path planning of UAV for oilfield inspections in a three-dimensional dynamic environment with moving obstacles based on an improved pigeon-inspired optimization algorithm
Alfeo et al. Enhancing biologically inspired swarm behavior: Metaheuristics to foster the optimization of UAVs coordination in target search
Levine et al. Learning robotic navigation from experience: principles, methods and recent results
Wen et al. Online UAV path planning in uncertain and hostile environments
Gul et al. Coordinated multi-robot exploration: Hybrid stochastic optimization approach
Kumar et al. Obstacle avoidance for a swarm of unmanned aerial vehicles operating on particle swarm optimization: A swarm intelligence approach for search and rescue missions
Lu et al. Global and local path planning of robots combining ACO and dynamic window algorithm
Yu et al. A novel sparrow particle swarm algorithm (SPSA) for unmanned aerial vehicle path planning
Mazaheri et al. A survey of 3D space path-planning methods and algorithms
Wolek et al. The Orbiting Dubins Traveling Salesman Problem: planning inspection tours for a minehunting AUV
Kumar et al. UAV swarm objectives: A critical analysis and comprehensive review
Chen et al. Social crowd navigation of a mobile robot based on human trajectory prediction and hybrid sensing
Pinkam et al. Rapid coverage of regions of interest for environmental monitoring
Arshid et al. Toward autonomous UAV swarm navigation: a review of trajectory design paradigms
Cao Simulation investigation of autonomous route planning for unmanned aerial vehicles based on an improved genetic algorithm
Kathen et al. Performance evaluation of AquaFeL-PSO informative path planner under different contamination profiles
Gul et al. Population‐Based Optimization With Decentralized Method
Bella et al. A hybrid air-sea cooperative approach combined with a swarm trajectory planning method
Lebedeva et al. Method for distributed mapping of terrain by a heterogeneous group of robots based on google cartographer