Sandwich Approach for Motion Planning and Control
Ramezani, Mohamadreza, Rastgoftar, Hossein
–arXiv.org Artificial Intelligence
This paper develops a new approach for robot motion planning and control in obstacle-laden environments that is inspired by fundamentals of fluid mechanics. For motion planning, we propose a novel transformation between motion space, with arbitrary obstacles of random sizes and shapes, and an obstacle-free planning space with geodesically-varying distances and constrained transitions. We then obtain robot desired trajectory by A* searching over a uniform grid distributed over the planning space. We show that implementing the A* search over the planning space can generate shorter paths when compared to the existing A* searching over the motion space. For trajectory tracking, we propose an MPC-based trajectory tracking control, with linear equality and inequality safety constraints, enforcing the safety requirements of planning and control.
arXiv.org Artificial Intelligence
Jan-10-2024
- Country:
- North America > United States > Arizona > Pima County > Tucson (0.14)
- Genre:
- Research Report (0.82)
- Technology: