32 citations · 72 across the 13 of their papers we have counts for
5 papers · 1 filter
State Representation Learning from Demonstration
Astrid Merckling, Alexandre Coninx, Loic Cressot +2
Robots could learn their own state and world representation from perception and experience without supervision. This desirable goal is the main focus of our field of interest, stat…
Unsupervised Learning and Exploration of Reachable Outcome Space
Giuseppe Paolo, Alban Laflaquière, Alexandre Coninx +1
Performing Reinforcement Learning in sparse rewards settings, with very little prior knowledge, is a challenging problem since there is no signal to properly guide the learning pro…
Building an Affordances Map with Interactive Perception
Leni K. Le Goff, Oussama Yaakoubi, Alexandre Coninx +1
Robots need to understand their environment to perform their task. If it is possible to pre-program a visual scene analysis process in closed environments, robots operating in an o…
Bootstrapping Robotic Ecological Perception from a Limited Set of Hypotheses Through Interactive Perception
Léni K. Le Goff, Ghanim Mukhtar, Alexandre Coninx +1
To solve its task, a robot needs to have the ability to interpret its perceptions. In vision, this interpretation is particularly difficult and relies on the understanding of the s…
From exploration to control: learning object manipulation skills through novelty search and local adaptation
Seungsu Kim, Alexandre Coninx, Stephane Doncieux
Programming a robot to deal with open-ended tasks remains a challenge, in particular if the robot has to manipulate objects. Launching, grasping, pushing or any other object intera…