NMPC for Collision Avoidance by Superellipsoid Separation
Fuente:
arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | |
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| _version_ | 1866910588887629824 |
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| author | Moran, Ruairi Bagley, Sheila Kasmann, Seth Martin, Rob Pasley, David Trimble, Shane Dianics, James Sopasakis, Pantelis |
| author_facet | Moran, Ruairi Bagley, Sheila Kasmann, Seth Martin, Rob Pasley, David Trimble, Shane Dianics, James Sopasakis, Pantelis |
| contents | This paper introduces a novel NMPC formulation for real-time obstacle avoidance on heavy equipment by modeling both vehicle and obstacles as convex superellipsoids. The combination of this approach with the separating hyperplane theorem and Optimization Engine (OpEn) allows to achieve efficient obstacle avoidance in autonomous heavy equipment and robotics. We demonstrate the efficacy of the approach through simulated and experimental results, showcasing a skid-steer loader's capability to navigate in obstructed environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_14257 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | NMPC for Collision Avoidance by Superellipsoid Separation Moran, Ruairi Bagley, Sheila Kasmann, Seth Martin, Rob Pasley, David Trimble, Shane Dianics, James Sopasakis, Pantelis Optimization and Control This paper introduces a novel NMPC formulation for real-time obstacle avoidance on heavy equipment by modeling both vehicle and obstacles as convex superellipsoids. The combination of this approach with the separating hyperplane theorem and Optimization Engine (OpEn) allows to achieve efficient obstacle avoidance in autonomous heavy equipment and robotics. We demonstrate the efficacy of the approach through simulated and experimental results, showcasing a skid-steer loader's capability to navigate in obstructed environments. |
| title | NMPC for Collision Avoidance by Superellipsoid Separation |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2404.14257 |