Receding Horizon Motion Planning for Multi-Agent Systems: A Velocity Obstacle Based Probabilistic Method
This addresses safer motion planning for multi-agent systems, particularly with high-speed agents, though it appears incremental as an extension of velocity obstacle methods with probabilistic constraints.
The paper tackles motion planning for multi-agent systems by developing a velocity obstacle-based probabilistic method that formulates chance constraints in receding horizon control, generating safer collision-free trajectories at the velocity level. Simulation results show it effectively avoids potential collisions with collision probability below a specific threshold.
In this paper, a novel and innovative methodology for feasible motion planning in the multi-agent system is developed. On the basis of velocity obstacles characteristics, the chance constraints are formulated in the receding horizon control (RHC) problem, and geometric information of collision cones is used to generate the feasible regions of velocities for the host agent. By this approach, the motion planning is conducted at the velocity level instead of the position level. Thus, it guarantees a safer collision-free trajectory for the multi-agent system, especially for the systems with high-speed moving agents. Moreover, a probability threshold of potential collisions can be satisfied during the motion planning process. In order to validate the effectiveness of the methodology, different scenarios for multiple agents are investigated, and the simulation results clearly show that the proposed approach can effectively avoid potential collisions with a collision probability less than a specific threshold.