Dr. Xuesu Xiao's main research aims at creating trustworthy, risk-aware, high-performance mobile robots working in challenging environments. He develops agile ground, aerial, and marine locomoters to be used for search and rescue missions in unstructured or confined environments, such as Hurricane Harvey and Fukushima Daiichi nuclear disaster response. From a robotics background, he is currently leveraging machine learning to further enhance mobile robots' capability.
Human-in the-Loop Machine Learning for Adaptive Robot Naviagtion
Inspection of City Infrastructure via Peripheral Perception
Research Labs & Affiliations:
Learning Agents Research Group (LARG)
Xuesu Xiao, Jan Dufek, Robin Murhy. April 2020. Robot Risk-Awareness by Formal Risk Reasoning and Planning. IEEE. IEEE Robotics and Automation Letters. 2856 - 2863.
Xuesu Xiao, Jan Dufek, Mohamed Suhail, Robin Murphy. October 2018. Motion Planning for a UAV with a Straight or Kinked Tether. IEEE. 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Xuesu Xiao, Jan Dufek, Tim Woodbury, Robin Murphy. September 2017. UAV assisted USV visual navigation for marine mass casualty incident response. IEEE. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Xuesu Xiao, Ellen Cappo, Weikun Zhen, Jin Dai, Ke Sun, Chaohui Gong, Matthew J. Traverse, Howie Choset. May 2015. Locomotive reduction for snake robots. IEEE. 2015 IEEE International Conference on Robotics and Automation (ICRA).