Simultaneous Path Planning and Task Allocation in Dynamic Environments

Abstract

This paper addresses the challenge of coordinating task allocation and generating collision-free trajectories for a fleet of mobile robots in dynamic environments. Our approach introduces an integrated framework comprising a centralized task allocation system and a distributed trajectory planner. The centralized task allocation system, employing a heuristic approach, aims to minimize the maximum spatial cost among the slowest robots. Tasks and trajectories are continuously refined using a distributed version of CHOMP (Covariant Hamiltonian Optimization for Motion Planning), tailored for multiple-wheeled mobile robots where the spatial costs are derived from a high-level global path planner. By employing this combined methodology, we are able to achieve near-optimal solutions and collision-free trajectories with computational performance for up to 50 robots within seconds.