RI: Small: Natural Language-Based Human Instruction for Task Embedded Robots

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This project will advance the scientific state of the art in social service robots by introducing a novel approach for performing, composing, and correcting tasks using spatial language, and for handling the challenges of long-term interaction with people. The team of investigators will leverage prior work on CoBot service robots as a scientific platform. CoBots can transport objects, deliver messages, escort people and go to places, continuously executing these tasks over multiple weeks in a multi-floor building. The team will collaborate to research, develop, and evaluate algorithms for learning, composing, and correcting the execution of tasks via natural language. The proposed research will enable any person to train the robot; we will use the CoBot robots to perform evaluation and testing of our proposed algorithms.The vision of a continuously operating robot in a real-world environment that can update its behavior in response to human instruction will have a broad impact on the way students, faculty and visitors interact with and view the usefulness of robots. Some examples include: (1) Customizable intelligent robots will give people the creative power to simply and intuitively update robot behavior, making the system broadly accessible to non-experts. (2) Outreach to the community will transform the view that robots are static unchangeable systems by creating an awareness towards robots co-inhabiting our environment. We will invite children of different age groups and people from different cultures to interact with our co-robot through language-based instruction. (3) Synergistic activities across multiple research groups have and will continue to be explored and encouraged (e.g., continuous environmental measurement and monitoring).