A moving obstacle avoidance strategy-based collaborative formation for the bionic multi-underwater spherical robot control system

The collaborative operation of multi-underwater robot formation is an effective way to deal with the complex underwater environment. A formation control strategy with high efficiency and accuracy in moving obstacle avoidance is very important. Based on the multi-robot experiment platform, a moving obstacle avoidance-constrained adaptive model predictive control (MOAC-AMPC) strategy is proposed for Underwater Spherical Robots (USRs). The strategy is optimized in two main aspects: Firstly, based on model predictive control, an adaptive weight matrix based on tracking error is designed to solve the tedious parameter tuning problem and reduce the tracking time. Then, the Velocity Obstacle (VO)-based dynamic constraints are designed to avoid multiple moving obstacles. Finally, the multi-underwater spherical robots experiment platform is built. Pool experiments are set up on the platform to verify the multi-robot formation with obstacles avoidance. The feasibility and superiority of the proposed strategy are verified by simulations and experiments. The application of the proposed multi-USRs strategy has certain practical value in multi-robot trajectory tracking and obstacle avoidance.