12 papers
Towards Robust Prehensile Manipulation in Open-Ended Environments
Mathilde Kappel, Mahdi Khoramshahi, Louis Annabi +2
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 wid…
A Sim-to-Real Integration Pipeline for Training and Deployment of Chunk-Based VLA Manipulation Policies
Mathilde Kappel, Clémence Grislain, Mohamed Chetouani +5
Vision-Language-Action (VLA) models have become a prominent paradigm for mapping multimodal inputs, including semantic instructions, visual observations of the scene, and proprioce…
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…
Fingertip Contact Force Direction Control using Tactile Feedback
Dounia Kitouni, Elie Chelly, Mahdi Khoramshahi +1
The human hand is an immensely sophisticated tool adept at manipulating and grasping objects of unknown characteristics. Its capability lies in perceiving interaction dynamics thro…
Robotic in-hand manipulation with relaxed optimization
Ali Hammoud, Valerio Belcamino, Quentin Huet +4
Dexterous in-hand manipulation is a unique and valuable human skill requiring sophisticated sensorimotor interaction with the environment while respecting stability constraints. Sa…
Speeding up 6-DoF Grasp Sampling with Quality-Diversity
Johann Huber, François Hélénon, Mathilde Kappel +4
Recent advances in AI have led to significant results in robotic learning, including natural language-conditioned planning and efficient optimization of controllers using generativ…
A model-free approach to fingertip slip and disturbance detection for grasp stability inference
Dounia Kitouni, Mahdi Khoramshahi, Veronique Perdereau
Robotic capacities in object manipulation are incomparable to those of humans. Besides years of learning, humans rely heavily on the richness of information from physical interacti…