We conduct interdisciplinary research aimed at discovering the principles underlying the design of artificially intelligent robots. Our goal is to create robots that can perform the kinds of everyday tasks that come naturally to humans, but that are beyond the reach of current technology.
Our research brings together ideas from motion and task planning, machine learning, reinforcement learning, and computer vision to synthesize robot systems that are capable of behaving intelligently across a wide range of problem domains. We are driven by the immense challenges faced by robots with imperfect sensors and incomplete knowledge of the world operating in unstructured environments.
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