Advancements in the field of robotics are fueled by research, which in turn heavily relies on effective platforms to test algorithms for robot control and navigation. While numerous robotics platforms have been developed over the past decades, most of them have shortcomings that limit their use in research settings.
Researchers at the University of California (UC) Berkeley recently developed Berkeley Humanoid, a new robotic platform that could be used to train and test algorithms for the control of humanoid robots. This new humanoid robot, introduced in a paper posted to the preprint server arXiv, addresses and overcomes some of the limitations of previously introduced robotics research platforms.
“Having conducted several experiments with commercially available robots, we have become aware of some of their weaknesses,” Qiayuan Liao, co-author of the paper, told Tech Xplore. “For instance, some robot hardware is very expensive, while other hardware is not designed especially for learning-based control or for research, which often means that it is ‘fragile,’ easy to break, and hard to maintain and repair.”
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