多机器人系统的曲率约束和恒速分布式同步到达控制
Simultaneous Arrival Control for Distributed Multi-Robot Systems with Curvature and Constant-Speed Constraints
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中文总结 AI 辅助
针对多机器人系统在曲率约束和恒速下同步到达目标点的难题，提出基于最大共识协议的分布式切换控制法，设计混合控制律，经仿真和实验验证了方法的有效性、鲁棒性等，还证明某些情况下可达理论最优到达时间。
中文摘要 AI 辅助
多移动机器人同时到达目标点对合作任务至关重要。当机器人轨迹曲率受限且速度需恒定时，该问题更具挑战性，且控制律需分布式。本文提出基于最大共识协议的分布式切换控制方法。利用Dubins路径几何特性引入虚拟时间变量，设计混合控制律。通过仿真和实验验证了方法的有效性、鲁棒性、可扩展性及实时性，还证明在某些情况下能达到理论最优到达时间。
英文摘要
The simultaneous arrival of multiple mobile robots at a target point is crucial for cooperation tasks such as cooperative encirclement, disaster relief, and environmental monitoring. Although the simultaneous arrival problem itself is already complex, the problem becomes more challenging when there are constraints on the robot trajectory curvatures and the speeds are required to be constant (possibly different for different robots), and the control law for robots needs to be distributed. These constraints are typical for a multi-robot system consisting of, e.g., fixed-wing UAVs. To address this challenge, this paper proposes a distributed switching control method based on the maximum consensus protocol. By exploiting the geometric properties of Dubins paths along with optimization principles, a virtual time variable is introduced, and a hybrid control law that combines optimal control with saturated proportional control is designed. Under the proposed control law, each robot is driven to approach the maximum virtual time among its neighbors, thereby achieving simultaneous arrival under some mild conditions. Furthermore, we prove that in certain cases the proposed method attains a theoretically optimal arrival time. The approach is scalable and real-time, with low communication overhead. Its effectiveness and robustness are validated through extensive simulations and experiments.
发表机构
- School of Artificial Intelligence and Robotics, Hunan University（湖南大学人工智能与机器人学院）
- College of Intelligence Science and Technology, National University of Defense Technology（国防科技大学智能科学与技术学院）
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