PhD Candidate, University of California, Berkeley
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Abstract
Designing Robot Behavior in Human-Robot Interactions
Human-robot interactions (HRI) have been recognized to be a key element of future robots in many application domains such as manufacturing, transportation, service and entertainment. These robots are called co-robots. Unlike traditional robots that work in structured and deterministic environments, co-robots need to operate in highly unstructured and stochastic environments. The fundamental research question is how to ensure that co-robots operate efficiently and safely in dynamic uncertain environments. In this poster, a multi-agent framework to model human-robot systems will be introduced. In order to address the uncertainties during human-robot interactions, a unique parallel planning and control architecture is proposed, which has a cognition module for human behavior estimation and human motion prediction, a long-term global planner to ensure efficiency of robot behavior, and a short-term local planner to ensure real-time safety under uncertainties. Fast optimization algorithms are developed to ensure timely responses in emergency situations, e.g. the convex feasible set algorithm (CFS) for the long-term optimization, and the safe set algorithm (SSA) for the short-term optimization. An application of the proposed method on automated vehicles will be discussed in the framework of the robustly safe automated driving (ROAD) system. Another application on industrial collaborative robots will be discussed in the framework of the robot safe interaction system (RSIS).
Bio
Changliu Liu is a Ph.D. candidate in the Department of Mechanical Engineering, University of California at Berkeley. She received the B.S. degree in mechanical engineering and the B.S. degree in economics from Tsinghua University (China) in 2012, and the M.S. degree in mechanical engineering and the M.A. degree in mathematics from University of California at Berkeley in 2014 and in 2016 respectively. Her research interests lie in the intersection of robotics, human-robot interactions, control and motion planning, optimal control and optimization, multi-agent system and game theory, machine learning and artificial intelligence. She was the recipient of the Chinese National Scholarship in 2010 and the Berkeley fellowship in 2012. Her Ph.D. work has been supported by the Berkeley fellowship, Denso International and FANUC Corporation.