An iterative optimization approach for multi-robot pattern formation in obstacle environment

Abstract Pattern formation for multi-robot systems has received increasing attention in different scenarios. However, existing methods cannot efficiently optimize pattern formation in the obstacle environment. To address this limitation, this paper proposes a new planning method that assigns the optimal goals to the robots and iteratively computes collision-free paths to reach goal positions. Firstly, according to the random initial position of the group robot and the arbitrary shape, convex quadratic programming is used to minimize the distance to obtain the optimal pattern parameters under certain constraints. Secondly, the iterative controller plans the collision-free path of each robot to the goal considering a preferred velocity. Simulation results verified the effectiveness of the proposed methodology for scenarios of letter formation, in comparison to a commonly-used method.