Institute of Robotics and Automatic Information System
Tianjin Key Laboratory of Intelligent Robotics
Seminar Series：Advanced Robotics & Artificial Intelligence
2022年12月20日（周二） 腾讯会议：519-672-145 入会密码：221220
Robot planning is not a new topic. Task planning is one of the earliest research areas in artificial intelligence, and motion planning is one of the most important topics in robotics. It was not until recently that researchers started to look into the so-called, task-and-motion planning (TAMP) problem, aiming to simultaneously fulfill task-level goals and ensure motion-level feasibility. Another observation is that, when such robots work with people, their observability gap makes collaboration difficult. In this talk, I first present grounded TAMP methods towards efficient and feasible task completions, and then present how we leverage augmented reality (AR) technologies to enable effective human-robot collaboration. Those methods are demonstrated using everyday robot tasks, such as mobile manipulation, and object delivery.
Dr. Shiqi Zhang is an Assistant Professor with the Department of Computer Science, the State University of New York (SUNY) at Binghamton. Before that, he was an Assistant Professor at Cleveland State University after working as a Postdoc at the University of Texas at Austin. He received his Ph.D. in Computer Science (2013) from Texas Tech University, and received his M.S. and B.S. degrees from Harbin Institute of Technology. He is leading a National Robotics Initiative project from the National Science Foundation on robot decision making. He received the Best Robotics Paper Award from the AAMAS-2018 conference, a Ford URP Award in 2019, and an OPPO Faculty Research Award in 2020. He was a Publication Co-chair of the AAMAS-2022 Conference, and is a Track Co-chair of the KR-2023 Conference.