Explores training robots through reinforcement learning and learning from demonstration, highlighting challenges in human-robot interaction and data collection.
Delves into using simulations for Human-Robot Interaction, learning from human expertise and preferences, user models, system models, simulation results, and assisting drone landings.
Explores turning bumper cars into unbumping ones through collision avoidance algorithms and the challenges faced when implementing ellipsoid barrier functions.
Explores the current challenges and advancements in object perception and manipulation in robotics, emphasizing the importance of context and user requirements.
Explores the boundary between hard coding and learning in robotics, emphasizing the importance of co-designing robotic hands and manipulation approaches to exploit environmental constraints.
