Justin Carpentier is a Researcher at Inria Paris within the WILLOW team. His research lies at the interface of Learning, Perception and Control for Robotics. From 2018 to 2019, he was a postdoctoral research associate in the same WILLOW team. He obtained a PhD degree from the University of Toulouse in Robotics in 2017.
Topics of interest
Robotics, Control, Vision, Optimization and Machine Learning.
Project in Prairie
The main scientific objective of Justin’s project within PRAIRIE is to lay the mathematical and algorithmic foundations to enable robotic systems (i) to learn precise model of their dynamics and their interactions and (ii) to exploit these learned models inside advanced control schemes in order to precisely achieve dynamic motions and solving complex tasks, all with an advanced level of autonomy and agility.
Despite major progress in mechatronics, planning, automatic control and perception over the past decades, current robots remain in overall limited in their capacity to comprehend and control the heterogeneous set of interactions with their environment. The overall ambition of Justin’s research is to enhance the robot capacities to precisely and safely interact with their surroundings in order to achieve fine manipulation gestures and agile locomotion, by leveraging recent progresses made in Vision, Machine Learning, Optimization and Control.