Adaptive obstacle avoidance control strategy for a formation under a narrow alleyway environment

This article develops an effective adaptive obstacle avoidance control strategy containing formation decision mechanism and a model predictive control-based formation controller for a multi-robot system working in a narrow alleyway environment. First, a decision mechanism containing two obstacle avoidance methods, homogeneous deformation and heterogeneous deformation, is established to provide a flexible choice for the formation to pass through the obstacle area, taking into account the formation safety and environment constraint. Furthermore, a formation bank is preset, and a performance evaluation system containing structural deformation, convergence speed, and energy consumption is established to help determine the best obstacle avoidance configuration. Then, a model predictive control-based formation controller with the leader-follower approach is utilized to realize the configuration switching and keeping. In the end, the simulation results verify the effectiveness of the proposed control strategy.

Automated summary

This article presents an adaptive obstacle avoidance control strategy for a multi-robot system in narrow alleyway environments. The strategy includes a formation decision mechanism and a model predictive control-based formation controller. The decision mechanism offers two obstacle avoidance methods, homogeneous deformation and heterogeneous deformation, to provide flexible options for the formation. A formation bank is preset to determine the best obstacle avoidance configuration based on structural deformation, convergence speed, and energy consumption. The proposed model predictive control-based formation controller ensures successful configuration switching and maintenance, as verified by simulation results.