Non-Conservative Obstacle Avoidance for Multi-Body Systems Leveraging Convex Hulls and Predicted Closest Points
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866912074659004416 |
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| author | Rassaerts, Lotte Suichies, Eke van de Vrande, Bram Alonso, Marco Meere, Bas Chong, Michelle Torta, Elena |
| author_facet | Rassaerts, Lotte Suichies, Eke van de Vrande, Bram Alonso, Marco Meere, Bas Chong, Michelle Torta, Elena |
| contents | This paper introduces a novel approach that integrates future closest point predictions into the distance constraints of a collision avoidance controller, leveraging convex hulls with closest point distance calculations. By addressing abrupt shifts in closest points, this method effectively reduces collision risks and enhances controller performance. Applied to an Image Guided Therapy robot and validated through simulations and user experiments, the framework demonstrates improved distance prediction accuracy, smoother trajectories, and safer navigation near obstacles. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_12659 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Non-Conservative Obstacle Avoidance for Multi-Body Systems Leveraging Convex Hulls and Predicted Closest Points Rassaerts, Lotte Suichies, Eke van de Vrande, Bram Alonso, Marco Meere, Bas Chong, Michelle Torta, Elena Robotics This paper introduces a novel approach that integrates future closest point predictions into the distance constraints of a collision avoidance controller, leveraging convex hulls with closest point distance calculations. By addressing abrupt shifts in closest points, this method effectively reduces collision risks and enhances controller performance. Applied to an Image Guided Therapy robot and validated through simulations and user experiments, the framework demonstrates improved distance prediction accuracy, smoother trajectories, and safer navigation near obstacles. |
| title | Non-Conservative Obstacle Avoidance for Multi-Body Systems Leveraging Convex Hulls and Predicted Closest Points |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.12659 |