Group for Research in Decision Analysis

Towards robust and intelligent robot motions in unstructured environments: planning and decision-making

Ye Zhao Georgia Institute of Technology, United States

The demand for autonomous, robust, intelligent robotic systems is growing rapidly, given their potential to make our societies more productive and increase our welfare. To achieve this, robots are increasingly expected to operate in human-populated environments, maneuver in remote and cluttered environments, maintain and repair facilities, take care of our health, and streamline manufacturing and assembly lines. However, computational issues limit the ability of robots to plan complex motions in constrained and contact-rich environments, interact with humans safely, and exploit dynamics to gracefully maneuver, manipulate, fly, or explore the oceans. This talk will be centered around planning and decision-making algorithms for robust and agile robots operating in complex environments. In particular, I will present novel computational approaches necessary to enable real-time and robust motion planning of highly dynamic bipedal locomotion over rough terrain. This planning approach revolves around robust disturbance metric, optimal recovery controller, and foot placement re-planning strategies. Extending this motion planning approach to generalized whole-body locomotion behaviors, I will talk about our recent progress on high-level reactive task planner synthesis for multi-contact, template-based locomotion interacting with constrained environments and how to integrate formal methods for mission-capable locomotion. This talk will also present robust trajectory optimization algorithm capable of handling contact uncertainties and without enumerating contact modes. I will end this talk with current research directions.

Bio: Ye Zhao is an Assistant Professor in The George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology starting in January 2019. He is affiliated with The Institute for Robotics and Intelligent Machines (IRIM). He received his Ph.D. degree in Mechanical Engineering from The University of Texas at Austin in 2016 and his bachelor degree from Harbin Institute of Technology in 2011. He was a postdoctoral fellow in SEAS, Harvard University. His research interests lie broadly in planning, decision-making, and optimization algorithms of highly dynamic, contact-rich, and human-centered robots. He is especially interested in challenging locomotion and manipulation problems with formal guarantees on robustness, agility, real-time, and autonomy. Ye's co-authored work has been recognized as the 2017 Thomson Reuters Highly Cited Paper and 2016 IEEE-RAS best whole-body control paper award finalist. He served as an ICT Chair of IROS 2018 and was a Co-Chair of the IEEE-RAS Student Activities Committee in 2016.

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