Herbert A. Simon University Professor
School of Computer Science, Carnegie Mellon University
Symbiotic Autonomous Service Robots: Learning and Transparency
We research on autonomous mobile robots with a seamless integration of perception, cognition, and action. In this talk, I will first introduce our CoBot service robots and their novel localization and symbiotic autonomy, which enable them to consistently move in our buildings, and learn from asking humans for help to overcome their limitations. I will then introduce multiple human-robot interaction contributions, including behavior learning by human instruction; planning for language-based complex commands; use of expressive lights to reveal the robot’s internal state; and the verbal explanation generation to describe the robot’s autonomous experience. I will conclude with a discussion of applications for mobile indoor service robots, and their potential impact.
Manuela M. Veloso is the Herbert A. Simon University Professor in the School of Computer Science at Carnegie Mellon University. She is the Head of the Machine Learning Department. She researches in Artificial Intelligence, Robotics, and Machine Learning. She founded and directs the CORAL research laboratory, for the study of autonomous agents that Collaborate, Observe, Reason, Act, and Learn, www.cs.cmu.edu/~coral. Professor Veloso is IEEE Fellow, AAAS Fellow, AAAI Fellow, Einstein Chair Professor, and the co-founder and past President of RoboCup, and past President of AAAI. Professor Veloso and her students research with a variety of autonomous robots, including mobile service robots and soccer robots. See www.cs.cmu.edu/~mmv for further information, including publications.
Professor Veloso’s lecture is co-hosted by the Institute for Robotics & Mechatronics (IRM) and the Department of Computer Science.
For more information or if you have an accommodation need please contact email@example.com
This lecture is open to the public. Space is limited and there is no registration; coming early is strongly recommended.