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Full Stream Name: Robot Learning from Demonstration and Interaction

Research Educator: Rudolf Lioutikov

Principal Investigator: Scott Niekum

Course options: Spring & Fall


How can robots be easily programmed by non-expert users in homes and workplaces?  How can robots learn to interpret and generalize human demonstrations?


Currently, most robots are programmed meticulously by robotics experts in a controlled laboratory setting—a model that is obviously not scalable to large-scale deployment.  Robot learning from demonstration has emerged as an alternative paradigm for teaching robots new tasks by simply showing them what to do, rather than by writing code.  Thus, learning from demonstration research tries to answer the question: “How can robots learn to interpret and generalize human demonstrations?”  Solving this core research problem will enable the next generation of personal robots to revolutionize the home and workplace in coming years.

This research stream will place students at the cutting-edge of robot learning from demonstration research, working with robots to perform complex manipulation tasks, such as autonomously building IKEA furniture.   Students will be given instruction in three core areas of robotics: manipulation, perception, and human-robot interaction.  Additionally, students will learn and practice programming skills via hands-on mini-projects in each of these areas. After these key competencies have been acquired, students will devise and implement research projects in the area of learning from demonstration.



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Computer Science, Math, Physics