Papers
13
Total Citations
507
H-Index
8
About
Yoan Mollard is a leading researcher at the intersection of intrinsically motivated learning, soft robotics, and human-robot collaboration. His most influential work, "Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum Learning" (175 citations), pioneers autotelic learning—where robots self-generate and self-select goals to autonomously build skill repertoires, a cornerstone of developmental robotics. Mollard has also made transformative contributions to assistive soft robotics, notably developing a compliant manipulator for elderly personal care (110 citations), and to ergonomic human-robot interaction, where his postural optimization framework (80 citations) directly improves worker safety and comfort. His work on programming by demonstration and feedback (39 citations) advances intuitive robot instruction for assembly tasks, while his multiagent reinforcement learning approach (36 citations) enables precise control of high-dimensional soft manipulators for surgical and assistive applications. Mollard’s research is distinguished by its practical focus on safe, collaborative robots that learn from and adapt to humans, with notable achievements including open-source platforms like Poppy and Explauto for autonomous exploration. His work continues to shape how robots become intuitive, safe, and autonomous partners in real-world environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Postural optimization for an ergonomic human-robot interaction80 citations · 2017
- 4Robot programming from demonstration, feedback and transfer39 citations · 2015
- 5
- 6Relational activity processes for modeling concurrent cooperation26 citations · 2016
- 7Impact of Robot Initiative on Human-Robot Collaboration13 citations · 2017
- 8
- 9
- 10