1. TriFinger: An Open-Source Robot for Learning Dexterity
- Author
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Wüthrich, M., Widmaier, F., Grimminger, F., Akpo, J., Joshi, S., Agrawal, V., Hammoud, B., Khadiv, M., Bogdanovic, M., Berenz, V., Viereck, J., Naveau, M., Righetti, L., Schölkopf, B., and Bauer, S.
- Subjects
FOS: Computer and information sciences ,Computer Science - Robotics ,Computer Science - Machine Learning ,Robotics (cs.RO) ,Machine Learning (cs.LG) - Abstract
Dexterous object manipulation remains an open problem in robotics, despite the rapid progress in machine learning during the past decade. We argue that a hindrance is the high cost of experimentation on real systems, in terms of both time and money. We address this problem by proposing an open-source robotic platform which can safely operate without human supervision. The hardware is inexpensive (about \SI{5000}[\$]{}) yet highly dynamic, robust, and capable of complex interaction with external objects. The software operates at 1-kilohertz and performs safety checks to prevent the hardware from breaking. The easy-to-use front-end (in C++ and Python) is suitable for real-time control as well as deep reinforcement learning. In addition, the software framework is largely robot-agnostic and can hence be used independently of the hardware proposed herein. Finally, we illustrate the potential of the proposed platform through a number of experiments, including real-time optimal control, deep reinforcement learning from scratch, throwing, and writing.
- Published
- 2020