2025
Task-Aware Robotic Grasping by evaluating Quality Diversity Solutions through Foundation Models
Aurel X. Appius, Émiland Garrabé, François Hélénon, Mahdi Khoramshahi, Mohamed Chetouani, Stéphane Doncieux
IROS 2025
Task-aware robotic grasping is a challenging problem that requires the integration of semantic understanding and geometric reasoning. This paper proposes a novel framework that leverages Large Language Models (LLMs) and Quality Diversity (QD) algorithms to enable zero-shot task-conditioned grasp syn