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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

Jan 22, 2020: Our paper titled "Controlling Assistive Robots with Learned Latent Actions" got accepted at ICRA 2020!
Jan 16, 2020: Our paper titled "Exchangeable Input Representations for Reinforcement Learning" got accepted at ACC 2020!
Dec 10, 2019: Erdem will be giving an oral presentation at CDC 2019 on "The Green Choice: Learning and Influencing Human Decisions on Shared Roads"!
Dec 1, 2019: Our paper titled "When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans" got accepted at HRI 2020!
Nov 12, 2019: We posted our new blogpost on "Controlling Assistive Robots with Learned Latent Actions".
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