Curvature-Constrained and Constant-Speed Distributed Simultaneous Arrival Control for Multi-Robot Systems
Robotics
Summary
The authors address the problem of multiple robots needing to reach the same point at the same time while moving at constant speeds and with limited turning ability, which is tougher for robots like fixed-wing drones. They created a new way for the robots to communicate and adjust their travel times using math related to the shortest routes a robot can take (Dubins paths) and control theory. Their method helps each robot adjust its timing based on what its nearby robots are doing, leading to simultaneous arrival under reasonable conditions. They also show the method can be optimal in some cases and works well in real-time with low communication needs. Their findings are supported by simulations and real experiments.
Authors
Zhouru Xiao, Yang Lu, Weijia Yao, Min Liu, Yaonan Wang
Abstract
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.