Layered virtual-leader DMPC with SQP for scalable V formation tracking of omni-robots in cluttered maps

Abstract

This paper proposes a hierarchical virtual leader based distributed model predictive control (DMPC) framework for V-formation control of omnidirectional mobile robots in static obstacle environments. The physical leader follows a predesigned reference trajectory, while the followers maintain the desired formation through distributed optimization. A layered communication topology is established, where only a subset of robots receives the leader’s predicted states and acts as virtual leaders for downstream followers. Each robot independently optimizes its control sequence using local neighbor information, enabling fully distributed coordination without centralized synchronization. The unified cost function considers formation maintenance, leader or virtual leader tracking, obstacle avoidance, and control effort. Static obstacles are represented on a grid map to ensure collision-free motion. Simulation results demonstrate that the proposed framework achieves accurate formation keeping, smooth trajectory tracking, and effective obstacle avoidance. The hierarchical virtual-leader architecture enhances scalability, coordination efficiency, and robustness for multi-robot formation systems.