Towards Robust Human-Robot Interaction: A Quality Diversity Approach - Robotics Institute Carnegie Mellon University
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RI Seminar

January

28
Fri
Stefanos Nikolaidis Assistant Professor Computer Science, University of Southern California
Friday, January 28
3:30 pm to 4:30 pm
Towards Robust Human-Robot Interaction: A Quality Diversity Approach

Abstract: The growth of scale and complexity of interactions between humans and robots highlights the need for new computational methods to automatically evaluate novel algorithms and applications. Exploring the diverse scenarios of interaction between humans and robots in simulation can improve understanding of complex human-robot interaction systems and avoid potentially costly failures in real-world settings. In this talk, I propose formulating the problem of automatic scenario generation in human-robot interaction as a quality diversity problem, where the goal is not to find a single global optimum, but a diverse range of failure scenarios that explore both environments and human actions. I show how standard quality diversity algorithms can discover surprising and unexpected failure cases in the shared autonomy domain. I then discuss the development of a new class of quality diversity algorithms that significantly improve the search of the scenario space and the integration of these algorithms with generative models, which enables the generation of complex and realistic scenarios. Finally, I discuss applications in procedural content generation and human preference learning.

Brief Bio: Stefanos Nikolaidis is an Assistant Professor of Computer Science at the University of Southern California and leads the Interactive and Collaborative Autonomous Robotics Systems (ICAROS) lab. His research draws upon expertise on artificial intelligence, human-robot interaction, procedural content generation and quality diversity optimization and leads to end-to-end solutions that enable deployed robotic systems to act robustly when interacting with people in practical, real-world applications. Stefanos completed his PhD at Carnegie Mellon’s Robotics Institute and received an MS from MIT, a MEng from the University of Tokyo and a BS from the National Technical University of Athens. His research has been recognized with an oral presentation at the Conference on Neural Information Processing Systems and best paper awards and nominations from the IEEE/ACM International Conference on Human-Robot Interaction, the International Conference on Intelligent Robots and Systems, and the International Symposium on Robotics.