8 papers
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…
Enhancing Robustness in Language-Driven Robotics: A Modular Approach to Failure Reduction
Ãmiland 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…
A tale of two goals: leveraging sequentiality in multi-goal scenarios
Olivier Serris, Stéphane Doncieux, Olivier Sigaud
Several hierarchical reinforcement learning methods leverage planning to create a graph or sequences of intermediate goals, guiding a lower-level goal-conditioned (GC) policy to re…
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…
Learning to explore when mistakes are not allowed
Charly Pecqueux-Guézénec, Stéphane Doncieux, Nicolas Perrin-Gilbert
Goal-Conditioned Reinforcement Learning (GCRL) provides a versatile framework for developing unified controllers capable of handling wide ranges of tasks, exploring environments, a…