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Stanford Intelligent and Interactive Autonomous Systems Group (ILIAD) develops algorithms for autonomous systems that safely and reliably interact with people. Using the tools from artificial intelligence, control theory, robotics, machine learning, and optimization, we develop practical algorithms and the theoretical foundations for interactive robots working with people in uncertain, and safety-critical environments.

Recent News

Nov 12, 2019: We posted our new blogpost on "Controlling Assistive Robots with Learned Latent Actions".
Oct 28, 2019: We posted our new blogpost on "Learning from My Partner's Actions: Roles in Decentralized Robot Teams".
Oct 24, 2019: TechXplore compiled a story about our work "Asking Easy Questions: A User-Friendly Approach to Active Reward Learning". Check it out here!
Sep 20, 2019: Check our R-AL submission about controlling assistive robots on arXiv.
Sep 11, 2019: Our papers titled "Asking Easy Questions: A User-Friendly Approach to Active Reward Learning", and "Learning from My Partner's Actions: Roles in Decentralized Robot Teams" got accepted at CoRL 2019!
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