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arXiv · 2610.06376

Towards Robust Prehensile Manipulation in Open-Ended Environments

Mathilde Kappel·Mahdi Khoramshahi·Louis Annabi·Faïz Ben Amar·Stéphane Doncieux
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Abstract

We propose to use Quality-Diversity (QD) algorithms to solve robotic prehensile manipulation tasks in open-ended environments. Our approach enables the efficient discovery of a wide range robust grasp configurations, which serve as reliable starting points for generating diverse prehensile manipulation trajectories on articulated objects. The resulting diversity in manipulation behaviors enhances generalization and adaptability, enabling effective deployment continuously evolving open-world settings.

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Mathilde Kappel, Mahdi Khoramshahi, Louis Annabi, Faïz Ben Amar, Stéphane Doncieux. 2026-10-05. Towards Robust Prehensile Manipulation in Open-Ended Environments. https://arxiv.org/abs/2610.06376

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