Adaptive UGVS Control for Crossing Corridors or Gaps with Self-Organized Formation

In this paper, an adaptive Unmanned Ground Vehicle swarm (UGVS) control for crossing corridors or gaps with self-organized formation is proposed to overcome the limitations of obstacle scenes. In traditional methods, obstacles are typically arranged in a regular and simplistic manner, often relying on global information for path planning, which makes it difficult to deal with more complex scenes. To tackle this problem, the authors propose a new control strategy to achieve efficient tracking and obstacle avoidance of UGVS in corridors or gaps environments. Firstly, a constraint model that considers the performance of tracking, obstacle avoidance, and formation maintenance is constructed, which is more suitable for obstacle scenes of complex corridors or gaps. Secondly, a new control framework based on the barrier Lyapunov function (BLF) is proposed to achieve tracking and obstacle avoidance of UGVS through constraint control. Meanwhile, a control strategy of UGVS for crossing corridors or gaps is designed, which avoids pre-training for specific obstacle scenes and cumbersome path planning for each individual. At last, the stability analysis is provided by the designed Lyapunov function. Simulation results of three different scenes verify the effectiveness of the proposed method.