[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Su et al., 2024 - Google Patents

A collaborative siege method of multiple unmanned vehicles based on reinforcement learning

Su et al., 2024

View HTML
Document ID
1597545985187033992
Author
Su M
Pu R
Wang Y
Yu M
Publication year

External Links

Snippet

A method based on multi-agent reinforcement learning is proposed to tackle the challenges to capture escaping Target by Unmanned Ground Vehicles (UGVs). Initially, this study introduces environment and motion models tailored for cooperative UGV capture, along with …
Continue reading at www.oaepublish.com (HTML) (other versions)

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
    • G05D1/0291—Fleet control
    • G05D1/0295—Fleet control by at least one leading vehicle of the fleet
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/10—Simultaneous control of position or course in three dimensions
    • G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
    • G05D1/104—Simultaneous control of position or course in three dimensions specially adapted for aircraft involving a plurality of aircrafts, e.g. formation flying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/04—Architectures, e.g. interconnection topology
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/0011—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot associated with a remote control arrangement
    • G05D1/0044—Control 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
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D2201/00—Application
    • G05D2201/02—Control of position of land vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run

Similar Documents

Publication Publication Date Title
Patle et al. Path planning in uncertain environment by using firefly algorithm
Liu et al. Multi-UAV path planning based on fusion of sparrow search algorithm and improved bioinspired neural network
Zhu et al. Complete coverage path planning of autonomous underwater vehicle based on GBNN algorithm
Xiang et al. Survey on fuzzy-logic-based guidance and control of marine surface vehicles and underwater vehicles
Duan et al. Imperialist competitive algorithm optimized artificial neural networks for UCAV global path planning
Xia et al. Cooperative task assignment and track planning for multi-UAV attack mobile targets
Mishra et al. Design of mobile robot navigation controller using neuro-fuzzy logic system
Sonny et al. Q-learning-based unmanned aerial vehicle path planning with dynamic obstacle avoidance
Tang et al. Path planning based on improved hybrid A* algorithm
Rubí et al. Quadrotor path following and reactive obstacle avoidance with deep reinforcement learning
Fan et al. Formation control of multiple unmanned surface vehicles using the adaptive null-space-based behavioral method
Cao et al. AUV Global Security Path Planning Based on a Potential Field Bio-Inspired Neural Network in Underwater Environment.
CN116448119A (en) A collaborative trajectory planning method for unmanned swarms facing sudden threats
Su et al. A collaborative siege method of multiple unmanned vehicles based on reinforcement learning
Wang et al. A multi-agent reinforcement learning algorithm with the action preference selection strategy for massive target cooperative search mission planning
CN115164890A (en) An autonomous motion planning method for swarm drones based on imitation learning
Zhao et al. A distributed model predictive control-based method for multidifferent-target search in unknown environments
Liang et al. Multi-UAV autonomous collision avoidance based on PPO-GIC algorithm with CNN–LSTM fusion network
Li et al. An Improved grey wolf optimizer with weighting functions and its application to Unmanned Aerial Vehicles path planning
Zhang et al. An improved particle swarm optimization based on age factor for multi-AUV cooperative planning
Zhou et al. Multi-robot collaborative hunting in cluttered environments with obstacle-avoiding Voronoi cells
Zhang et al. DRL-based target interception strategy design for an underactuated USV without obstacle collision
Sun et al. A Fuzzy-Based Bio-Inspired Neural Network Approach for Target Search by Multiple Autonomous Underwater Vehicles in Underwater Environments.
Ma et al. Path planning and task assignment of the multi-AUVs system based on the hybrid bio-inspired SOM algorithm with neural wave structure
Lindqvist et al. Collision avoidance for multiple micro aerial vehicles using fast centralized nonlinear model predictive control