Sandwich Approach for Motion Planning and Control
Fuente:
arXiv
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866909068246908928 |
|---|---|
| author | Ramezani, Mohamadreza Rastgoftar, Hossein |
| author_facet | Ramezani, Mohamadreza Rastgoftar, Hossein |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_16874 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Sandwich Approach for Motion Planning and Control Ramezani, Mohamadreza Rastgoftar, Hossein Robotics Systems and Control 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. |
| title | Sandwich Approach for Motion Planning and Control |
| topic | Robotics Systems and Control |
| url | https://arxiv.org/abs/2309.16874 |