Real-Time-Feasible Collision-Free Motion Planning For Ellipsoidal Objects

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Gao, Yunfan, Messerer, Florian, van Duijkeren, Niels, Houska, Boris, Diehl, Moritz
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866908336980492288
author Gao, Yunfan
Messerer, Florian
van Duijkeren, Niels
Houska, Boris
Diehl, Moritz
author_facet Gao, Yunfan
Messerer, Florian
van Duijkeren, Niels
Houska, Boris
Diehl, Moritz
contents Online planning of collision-free trajectories is a fundamental task for robotics and self-driving car applications. This paper revisits collision avoidance between ellipsoidal objects using differentiable constraints. Two ellipsoids do not overlap if and only if the endpoint of the vector between the center points of the ellipsoids does not lie in the interior of the Minkowski sum of the ellipsoids. This condition is formulated using a parametric over-approximation of the Minkowski sum, which can be made tight in any given direction. The resulting collision avoidance constraint is included in an optimal control problem (OCP) and evaluated in comparison to the separating-hyperplane approach. Not only do we observe that the Minkowski-sum formulation is computationally more efficient in our experiments, but also that using pre-determined over-approximation parameters based on warm-start trajectories leads to a very limited increase in suboptimality. This gives rise to a novel real-time scheme for collision-free motion planning with model predictive control (MPC). Both the real-time feasibility and the effectiveness of the constraint formulation are demonstrated in challenging real-world experiments.
format Preprint
id arxiv_https___arxiv_org_abs_2409_12007
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Real-Time-Feasible Collision-Free Motion Planning For Ellipsoidal Objects
Gao, Yunfan
Messerer, Florian
van Duijkeren, Niels
Houska, Boris
Diehl, Moritz
Robotics
Systems and Control
Online planning of collision-free trajectories is a fundamental task for robotics and self-driving car applications. This paper revisits collision avoidance between ellipsoidal objects using differentiable constraints. Two ellipsoids do not overlap if and only if the endpoint of the vector between the center points of the ellipsoids does not lie in the interior of the Minkowski sum of the ellipsoids. This condition is formulated using a parametric over-approximation of the Minkowski sum, which can be made tight in any given direction. The resulting collision avoidance constraint is included in an optimal control problem (OCP) and evaluated in comparison to the separating-hyperplane approach. Not only do we observe that the Minkowski-sum formulation is computationally more efficient in our experiments, but also that using pre-determined over-approximation parameters based on warm-start trajectories leads to a very limited increase in suboptimality. This gives rise to a novel real-time scheme for collision-free motion planning with model predictive control (MPC). Both the real-time feasibility and the effectiveness of the constraint formulation are demonstrated in challenging real-world experiments.
title Real-Time-Feasible Collision-Free Motion Planning For Ellipsoidal Objects
topic Robotics
Systems and Control
url https://arxiv.org/abs/2409.12007