Cited by Object Manipulation in Marine Environments using Reinforcement Learning

Neurodynamics-Based Attack-Defense Guidance of Autonomous Surface Vehicles Against Multiple Attackers for Domain Protection DOI

Tong Kang, Nan Gu, Dan Wang

et al.

IEEE Transactions on Industrial Electronics, Journal Year: 2024, Volume and Issue: 71(10), P. 12655 - 12663

Published: Feb. 14, 2024

This article investigates an adversarial domain protection scenario involving multiple defending underactuated autonomous surface vehicles (ASVs) against equal number of attacking ASVs in obstructive environment. The can only obtain the positions susceptible stochastic measurement noises. A three-layer attack-defense guidance structure is proposed such that are able to intercept with collision-free behaviors. In first layer, auction theory utilized achieve matching efficiently assigns corresponding a distributed manner. second adaptive method proposed, enabling each ASV implement appropriate law aligned optimal interception point. last quadratic programming problem formulated using speed-heading-constraint control barrier functions, and neurodynamics optimization approach employed real-time resolution signal. stability safety analyses show system error practically input-to-state stable, guaranteed be safe. Experiment results demonstrate effectiveness neurodynamics-based for protection.

Language: Английский

Citations

Fully Distributed Target Encircling Control of Autonomous Surface Vehicles Based on Noncooperative Games DOI

Yue Jiang, Zhongkui Li

IEEE Transactions on Intelligent Vehicles, Journal Year: 2024, Volume and Issue: 9(4), P. 4769 - 4779

Published: March 4, 2024

This paper addresses cooperative target encircling of multiple autonomous surface vehicles (ASVs) with private and potentially competitive objectives. A fully distributed control approach is proposed based on noncooperative games. Specifically, a estimator an adaptive gain developed to estimate the information without using global state or topology knowledge. Based low-frequency learning technique, fuzzy predictor presented approximate unknown vehicle kinematics induced by uncertain nonlinearities environmental disturbances. By decoupling into task spacing task, law are designed Nash equilibrium seeking for achieving objective each ASV. The input-to-state stability closed-loop system proven via cascade analysis. Simulation results provided illustrate effectiveness game-based method ASVs in circumnavigation missions.

Language: Английский

Citations

Parallel Path Following of Under-Actuated Cyber-Physical Autonomous Surface Vehicles Based on Meta-Learning Extended State Observer DOI

Jiaxue Xu, Fengbei Xia, Nan Gu

et al.

IEEE Transactions on Vehicular Technology, Journal Year: 2024, Volume and Issue: 73(11), P. 16041 - 16050

Published: July 18, 2024

Language: Английский

Citations

Saturation-Tolerant Tunnel Prescribed Control for Vessel-Train Formation of Underactuated MSVs DOI

Wentao Wu, Yibo Zhang, Weidong Zhang

et al.

IEEE Transactions on Vehicular Technology, Journal Year: 2024, Volume and Issue: 73(12), P. 18380 - 18390

Published: Aug. 28, 2024

Language: Английский

Citations

Dynamic performance-guaranteed adaptive event-triggered trajectory tracking control for underactuated surface vehicles DOI

Yuan Lin, Zehua Jia, Dongsheng Guo

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 312, P. 119114 - 119114

Published: Aug. 30, 2024

Language: Английский

Citations

USV-Tracker: A novel USV tracking system for surface investigation with limited resources DOI

Tao Huang, Yiheng Xue, Zhenfeng Xue

et al.

Ocean Engineering, Journal Year: 2024, Volume and Issue: 312, P. 119196 - 119196

Published: Sept. 14, 2024

Language: Английский

Citations

Object Manipulation in Marine Environments using Reinforcement Learning DOI

Ahmed Nader,

Muhayy Ud Din,

Mughni Irfan

et al.

IFAC-PapersOnLine, Journal Year: 2024, Volume and Issue: 58(20), P. 215 - 222

Published: Jan. 1, 2024

Language: Английский

Citations