Year: 2025
Type: article
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.
Source: Robotics
Authors: Jennifer David, Rafael Valencia
Institution: Halmstad University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,172
OpenAlex ID: W4407104181