This paper introduces a novel NMPC formulation for real-time obstacle avoidance on heavy equipment by modeling both vehicle and obstacles as convex superellipsoids. The combination of this approach with the separating hyperplane theorem and Optimization Engine (OpEn) allows to achieve efficient obstacle avoidance in autonomous heavy equipment and robotics. We demonstrate the efficacy of the approach through simulated and experimental results, showcasing a skid-steer loader's capability to navigate in obstructed environments.
Cite
@article{arxiv.2404.14257,
title = {NMPC for Collision Avoidance by Superellipsoid Separation},
author = {Ruairi Moran and Sheila Bagley and Seth Kasmann and Rob Martin and David Pasley and Shane Trimble and James Dianics and Pantelis Sopasakis},
journal= {arXiv preprint arXiv:2404.14257},
year = {2024}
}