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This paper tackles the simultaneous arrival problem for multi-robot systems under the constraints of constant speed and curvature-limited trajectories, which are critical for applications like disaster relief. By employing a distributed switching control method based on the maximum consensus protocol and leveraging the geometric properties of Dubins paths, the authors introduce a hybrid control law that effectively coordinates the robots' movements. The proposed method not only ensures simultaneous arrival but also achieves optimal arrival times in certain scenarios, demonstrating scalability and low communication overhead through extensive simulations and experiments.
Achieving simultaneous arrival for multi-robot systems with curvature and speed constraints could revolutionize cooperative tasks in dynamic environments.
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.
