How can I build a safe, efficient multi-drone delivery system?
Cooperative Control of Multi-Quadrotors for Transporting Cable-Suspended Payloads: Obstacle-Aware Planning and Event-Based Nonlinear Model Predictive Control
This paper proposes a system for controlling multiple quadrotors to cooperatively transport a cable-suspended payload, navigating a 3D environment with static and dynamic obstacles. It combines an event-triggered control system with Nonlinear Model Predictive Control (NMPC) and an A* path planning algorithm. The system uses data from both conventional and event cameras to detect obstacles and update its environment map, triggering recalculations of the quadrotor trajectories only when necessary.
Key points relevant to LLM-based multi-agent systems include the decentralized nature of the quadrotor control, the integration of planning and control using A* and NMPC, the adaptive response to dynamic environments using event-triggered updates, and the potential for enhanced coordination and decision-making in multi-agent systems. Although the research doesn't directly use LLMs, the core concepts of multi-agent planning, control, and adaptation are applicable to LLM-based agent development, especially in scenarios requiring real-time responses to dynamic and complex environments. The event-driven approach could also inspire LLM-based agents that only process information when significant changes occur, potentially enhancing efficiency.