English

SCTOMP: Spatially Constrained Time-Optimal Motion Planning

Robotics 2023-07-18 v2 Optimization and Control

Abstract

This paper focuses on spatial time-optimal motion planning, a generalization of the exact time-optimal path following problem that allows the system to plan within a predefined space. In contrast to state-of-the-art methods, we drop the assumption that a collision-free geometric reference is given. Instead, we present a two-stage motion planning method that solely relies on a goal location and a geometric representation of the environment to compute a time-optimal trajectory that is compliant with system dynamics and constraints. To do so, the proposed scheme first computes an obstacle-free Pythagorean Hodograph parametric spline, and second solves a spatially reformulated minimum-time optimization problem. The spline obtained in the first stage is not a geometric reference, but an extension of the environment representation, and thus, time-optimality of the solution is guaranteed. The efficacy of the proposed approach is benchmarked by a known planar example and validated in a more complex spatial system, illustrating its versatility and applicability.

Keywords

Cite

@article{arxiv.2210.02345,
  title  = {SCTOMP: Spatially Constrained Time-Optimal Motion Planning},
  author = {Jon Arrizabalaga and Markus Ryll},
  journal= {arXiv preprint arXiv:2210.02345},
  year   = {2023}
}

Comments

This paper has been accepted for publication at the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Detroit, USA, October 2023. Copyright @ IEEE

R2 v1 2026-06-28T02:51:51.957Z