Decentralized Ability-Aware Adaptive Control for Multi-Robot Collaborative Manipulation

Multi-robot teams can achieve more dexterous, complex and heavier payload tasks than a single robot, yet effective collaboration is required. extremely challenging due to the different kinematic dynamics capabilities of robots, limited communication between them, uncertainty system parameters. In this letter, Decentralized Ability-Aware Adaptive Control (DA 3 C) proposed address these challenges based on two key features. Firstly, common manipulation task represented by nominal ellipsoid, which used maximize each robot's force capability online via optimizing its configuration. Secondly, decentralized adaptive controller designed be Lyapunov stable in spite heterogeneous actuation constraints robots uncertain physical parameters object environment. framework, coordination load distribution achieved without communication, while only control deficiency broadcast if any reaches limits. case, object's reference trajectory modified manner guarantee interaction. Finally, we perform several numerical simulations analyse verify method with multi-robot collaborative tasks.