Correct Me if I am Wrong: Interactive Learning for Robotic Manipulation
| Autor: | Eugenio Chisari, Tim Welschehold, Joschka Boedecker, Wolfram Burgard, Abhinav Valada |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Human-Computer Interaction Computer Science - Robotics Control and Optimization Artificial Intelligence Control and Systems Engineering Mechanical Engineering Biomedical Engineering Computer Vision and Pattern Recognition Robotics (cs.RO) Computer Science Applications |
| Popis: | Learning to solve complex manipulation tasks from visual observations is a dominant challenge for real-world robot learning. Although deep reinforcement learning algorithms have recently demonstrated impressive results in this context, they still require an impractical amount of time-consuming trial-and-error iterations. In this work, we consider the promising alternative paradigm of interactive learning in which a human teacher provides feedback to the policy during execution, as opposed to imitation learning where a pre-collected dataset of perfect demonstrations is used. Our proposed CEILing (Corrective and Evaluative Interactive Learning) framework combines both corrective and evaluative feedback from the teacher to train a stochastic policy in an asynchronous manner, and employs a dedicated mechanism to trade off human corrections with the robot's own experience. We present results obtained with our framework in extensive simulation and real-world experiments to demonstrate that CEILing can effectively solve complex robot manipulation tasks directly from raw images in less than one hour of real-world training. Accepted for publication in RA-L. Video, code and models available at http://ceiling.cs.uni-freiburg.de/ |
| Databáze: | OpenAIRE |
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