Distributed Formation Control for Autonomous Robots in Dynamic Environments
This addresses the challenge of coordinated robot navigation in unpredictable settings, which is incremental as it builds on existing formation control methods with specific enhancements for obstacle handling.
The paper tackles the problem of controlling autonomous robots to maintain formations while tracking a moving target in dynamic environments, achieving this through a distributed method that uses artificial force fields for convergence and obstacle avoidance, with stability proven via Lyapunov analysis and effectiveness demonstrated in V-shape and circular formations.
In this paper, we propose a novel and distributed formation control method for autonomous robots to follow the desired formation while tracking a moving target in dynamic environments. In our approach, the desired formations, which include the virtual nodes arranged into specific shapes, are first generated. Then, autonomous robots are controlled by the proposed artificial force fields in order to converge to these virtual nodes without collisions. The stability analysis based on the Lyapunov approach is given. Moreover, a new combination of rotational force field and repulsive force field in designing an obstacle avoidance controller allows the robot to avoid and escape the convex and nonconvex obstacle shapes. The V-shape and circular shape formations with their advantages are utilized to test the effectiveness of the proposed method.