Research Assisstants Zhihao Zhang(张智豪) Feb 2024 – Present Undergraduate in Computer Science and Technology, Heilongjiang University of Science and Technology Research Interest: Autonomous Systems, Motion Planning
Research Assisstants
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Research Assisstants Yueteng Yang(杨跃腾) October 2023 – Present Research Interest: SLAM
Research Assisstants Hangtian Zhao(赵杭天) September 2023 – Present Graduated in Shanghai Institute of Applied Physics, University of Chinese Academy of Sciences Undergraduate in School of Opto-Electronic Science and Engineering, University of Electronic Science and Technology of China Research Interest: Depth Estimation, Object Tracking, Software Engineer
Research Assisstants Guangtong Xu (徐广通) Ph.D in School of Aerospace Engineering, Beijing Institute of Technology, 2015-2021 Post-doc in Department of Precision Instrument, Tsinghua University, 2021-2023 Research Interest: Autonomous Navigation of Swarm Robotics
RESEARCH ASSISSTANTS Kaixin Chai(柴凯昕) October 2022 – Present Undergraduate in Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University Interest: SLAM, Motion Planning, Control
RESEARCH ASSISSTANTS Xuankang Wu(吴选康) July 2022 – Present Undergraduate in Robot Engineering, Northeastern University Multi-Sensor Fusion, VIO , Motion Planning
Research Assisstants Xuan Zheng (郑萱) November 2021 – Present Master Candidate, ZJU College of Control science and engineering BE in Electrical Engineering, Zhejiang University, 2019
Research Assisstants Fan Yang (杨帆) Sep 2021 – Present Robotics Engineer in RoboMaster, DJI from 2017 to 2021 BE in Communication Engineering, Southern University of Science and Technology, 2017 Research Interest: Mobile Robots, Motion and Path Planning
Research Assisstants Jiaying Ren (任家莹) August 2021 – Present BA in Journalism, Zhejiang University, 2021
Research Assisstants Jinghang Li (李景行) July 2021 – Present MS in Mechanical Engineering, Beijing Institute of Technology, 2021 BS in Vehicle Engineering, China Agricultural University, 2018 Research Interest: intelligent vehicles, deep learning, motion planning