USARSim group at NIST developed a simulated robot that operated in the Unreal Tournament 3 (UT3) gaming environment. They used a software PID controller to control the robot in UT3 worlds. Unfortunately, the PID controller did not work well, so NIST asked us to develop a better controller using machine learning techniques. In the process, we characterized the software PID controller and the robot’s behavior in UT3 worlds. Using data collected from our simulations, we compared different machine learning techniques including linear regression and reinforcement learning (RL). Finally, we implemented a RL based controller in Matlab and ran it in the UT3 environment via a TCP/IP link between Matlab and UT3.
- Design Engineering Division and Computers and Information in Engineering Division
Controlling a Simulated Robot Using Machine Learning Techniques
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Becker, J, Purohit, A, & Sun, Z. "Controlling a Simulated Robot Using Machine Learning Techniques." Proceedings of the ASME 2010 World Conference on Innovative Virtual Reality. ASME 2010 World Conference on Innovative Virtual Reality. Ames, Iowa, USA. May 12–14, 2010. pp. 1-10. ASME. https://doi.org/10.1115/WINVR2010-3705
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