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arXiv · 2410.12659

Non-Conservative Obstacle Avoidance for Multi-Body Systems Leveraging Convex Hulls and Predicted Closest Points

Lotte Rassaerts·Eke Suichies·Bram van de Vrande·Marco Alonso·Bas Meere·Michelle Chong·Elena Torta
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Abstract

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.

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Lotte Rassaerts, Eke Suichies, Bram van de Vrande, Marco Alonso, Bas Meere, Michelle Chong, Elena Torta. 2024-10-16. Non-Conservative Obstacle Avoidance for Multi-Body Systems Leveraging Convex Hulls and Predicted Closest Points. https://arxiv.org/abs/2410.12659

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