SCTOMP: Spatially Constrained Time-Optimal Motion Planning
Arrizabalaga, Jon, Ryll, Markus
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Jul-15-2023
- Country:
- North America > United States (0.14)
- Europe > Germany
- Bavaria > Upper Bavaria > Munich (0.04)
- Genre:
- Research Report > Promising Solution (0.34)
- Technology: