10 papers
Autonomously Acquiring Robot Manipulation Skills with Language-Driven Quality-Diversity
Émiland Garrabé, Mahdi Khoramshahi, Stéphane Doncieux
Quality-diversity (QD) algorithms have been gaining traction in robot learning, where diverse motion primitive libraries allow robots to adapt zero-shot to constraints at deploymen…
QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation
Mathilde Kappel, Mahdi Khoramshahi, Louis Annabi +2
Thanks to the latest advances in learning and robotics, domestic robots are beginning to enter homes, aiming to execute household chores autonomously. However, robots still struggl…
Placeit! A Framework for Learning Robot Object Placement Skills
Amina Ferrad, Johann Huber, François Hélénon +3
Robotics research has made significant strides in learning, yet mastering basic skills like object placement remains a fundamental challenge. A key bottleneck is the acquisition of…
Task-Aware Robotic Grasping by evaluating Quality Diversity Solutions through Foundation Models
Aurel X. Appius, Emiland Garrabe, Francois Helenon +3
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 lev…
Tactile-based force estimation for interaction control with robot fingers
Elie Chelly, Andrea Cherubini, Philippe Fraisse +2
Fine dexterous manipulation requires reactive control based on rich sensing of manipulator-object interactions. Tactile sensing arrays provide rich contact information across the m…
Enhancing Robustness in Language-Driven Robotics: A Modular Approach to Failure Reduction
Émiland Garrabé, Pierre Teixeira, Mahdi Khoramshahi +1
Recent advances in large language models (LLMs) have led to significant progress in robotics, enabling embodied agents to better understand and execute open-ended tasks. However, e…