2024
Talk Through It: End User Directed Manipulation Learning
RA-L 2024
Training robots to perform a huge range of tasks in many different environments is immensely difficult. Instead, we propose selectively training robots based on end-user preferences. Given a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">factory mod