LF: Online Multi-Robot Path Planning Meets Optimal Trajectory Control

TL;DR

This paper introduces LF, a hierarchical multi-robot navigation framework combining fast multi-agent pathfinding with dynamics-aware control, enabling scalable, reliable, and adaptable multi-robot navigation in dynamic environments.

Contribution

The paper presents LF, a novel hierarchical control paradigm integrating discrete MAPF planning with continuous trajectory control for scalable multi-robot navigation.

Findings

Successfully deployed 15 multirotors with real-time target updates

Achieved collision-free, deadlock-free navigation in dynamic environments

Demonstrated robustness and adaptability in real-world experiments

Abstract

We propose a multi-robot control paradigm to solve point-to-point navigation tasks for a team of holonomic robots with access to the full environment information. The framework invokes two processes asynchronously at high frequency: (i) a centralized, discrete, and full-horizon planner for computing collision- and deadlock-free paths rapidly, leveraging recent advances in multi-agent pathfinding (MAPF), and (ii) dynamics-aware, robot-wise optimal trajectory controllers that ensure all robots independently follow their assigned paths reliably. This hierarchical shift in planning representation from (i) discrete and coupled to (ii) continuous and decoupled domains enables the framework to maintain long-term scalable motion synthesis. As an instantiation of this idea, we present LF, which combines a fast state-of-the-art MAPF solver (LaCAM), and a robust feedback control stack (Freyja) for executing agile robot maneuvers. LF provides a robust and versatile mechanism for lifelong multi-robot navigation even under asynchronous and partial goal updates, and adapts to dynamic workspaces simply by quick replanning. We present various multirotor and ground robot demonstrations, including the deployment of 15 real multirotors with random, consecutive target updates while a person walks through the operational workspace.