Interactive Decision-making and Resilient Planning for Safe Legged Locomotion and Navigation
Ye Zhao Wins NSF CAREER Award for “Interactive Decision-making and Resilient Planning for Safe Legged Locomotion and Navigation”
July 12, 2022
By: Christa M. Ernst
Dr. Ye Zhao, Assistant Professor at the George W. Woodruff School of Mechanical Engineering, Director of the Laboratory for Intelligent Decision and Autonomous Robots (LIDAR) and member of the Institute for Robotics and Intelligent Machines, has been granted an NSF CAREER Award of ~$595,000.00 over a period of 5 years. Ye and his team will use the funding to develop a novel task and motion planning framework for bipedal robotic locomotion interacting with complex environments. Prof. Zhao’s goal is to achieve safe and autonomous robot locomotion that will move legged robotic systems from the confines of research labs into real-world application domains such as disaster relief, first responder assistance, surveillance for civil and mechanical infrastructures, and use in agricultural environments.
Zhao and his team aim to apply full-body-dynamics-aware trajectory optimization techniques with symbolic planning and policy learning, formal task specification design, robust decision-making, and add real-time locomotion failure recovery capability via behavior trees to address unexpected environment interventions. By using these complementary methods, Prof. Zhao hopes to resolve computational hurdles that have hindered the use of symbolic planning and decision-making methodologies on human-robot interaction problems. Additionally, Zhao and the LIDAR team will place and emphasis on experimental evaluations to enable transformative new legged navigation functionalities in real-world scenarios and pave the road for future studies of heterogeneous robot teaming in challenging environments.
Ye Zhao received his Ph.D. degree in Mechanical Engineering from The University of Texas at Austin in 2016 and was a Postdoctoral Fellow at Harvard University, where he worked on robust trajectory optimization algorithms for manipulation problems with frictional contact behaviors. Dr. Zhao's and his students’ recent work has been recognized as 2021 ICRA Best Paper Award Finalist in Automation, 2016 IEEE-RAS best whole-body control paper award finalist, 2020 Late Breaking Results Best Poster Award, IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), and 2017 Thomson Reuters Highly Cited Paper. He serves as an Associate Editor of IEEE-RAS Robotics and Automation Letters and IEEE Control Systems Letters.
At the Laboratory for Intelligent Decision and Autonomous Robots Zhao and his team focus on the theoretical and algorithmic underpinnings for collaborative humanoid and mobile robots operating in unstructured and unpredictable environments while working alongside humans. Over the past few years, his team has enjoyed the collaborations with other research labs exploring machine learning, multi-agent teaming and safety control, and soft robotics. They look forward to working with people from physical human-robot interaction, contact mechanics, and animal behavior analysis areas.
About the NSF CAREER Award
The Faculty Early Career Development (CAREER) Program offers the National Science Foundation's most prestigious awards in support of early-career faculty who have the potential to serve as academic role models in research and education and to lead advances in the mission of their department or organization. Activities pursued by early-career faculty build a firm foundation for a lifetime of leadership in integrating education and research.