How can I plan robot arm & base movements for cooperative object transport?
Motion Planning of Nonholonomic Cooperative Mobile Manipulators
This paper proposes a two-step motion planning technique for multiple mobile manipulator robots (MMRs) cooperatively transporting an object in environments with static and dynamic obstacles. An offline planner finds a collision-free path, and an online planner uses nonlinear model predictive control (NMPC) to generate dynamically feasible, collision-free trajectories, respecting robot constraints and object rigidity.
For LLM-based multi-agent systems, this research is relevant due to its focus on: (1) Decentralized control: Each MMR acts as an independent agent with localized perception and planning. (2) Constraint satisfaction: The NMPC approach addresses real-world constraints relevant to embodied agents, such as kinematics and collision avoidance. (3) Dynamic environments: The system adapts to changes in the environment, an essential capability for real-world multi-agent applications. (4) Cooperation: Agents collaborate on a shared task (object transportation) by maintaining formation and avoiding collisions. This could translate to complex task completion in LLM-based multi-agent systems.