Welcome to the SUSTech
Control & Learning for Robotics and Autonomy(CLEAR) Lab

News

  • New paper on optimal control of SLIP model

    Our new paper entitled “Optimal Control of a Differentially Flat 2D Spring-Loaded Inverted Pendulum Model” is accepted by IEEE Robotics and Automation Letters (RA-L). We study the optimal control problem of an

  • Our New Quadruped Robot!

    Take a look at our in-house built quadruped robot with customized motor and body designs. It is designed and built mostly by Shenggao Li (an undergraduate student in our lab). It is

  • New result on Dynamic Walking using Reinforcement Learning

    We present a novel model-free reinforcement learning (RL) framework to design feedback control policies for 3D bipedal walking. Existing RL algorithms are often trained in an end-to-end manner or rely on prior

  • Prof. Dongrui Wu (HZUST) visited our lab

    Prof. Dongrui Wu visited our lab at and gave a talk, entitled “Fuzzy Logic and Signal Processing/Machine Learning for Brain-Computer Interface (BCI)”. Prof. Wu is currently a Professor at the School of

  • Prof. Jing Sun (UMich) visited our lab

    Prof. Jing Sun visited our lab and discussed possible research collaborations in control and robotics. Prof. Sun is currently the Michael G. Parsons Collegiate Professor and the Department Chair of the Naval

  • Invited Speaker @ CACRE 2019

    Prof. Zhang was invited to attend and gave an invited talk at the 2019 International Conference on Automation, Control and Robotics Engineering, held between July 19 – July 21, in Shenzhen, China.

Welcome to the SUSTech Control & Learning for Robotics and Autonomy (CLEAR) Lab. Our lab develops new theoretic and algorithmic tools in control and learning theory to enable advanced applications in modern robotic and autonomous systems.

Our research crosscuts various areas, including underwater robotics, legged locomotion control, autonomous system navigation and collision avoidance, dynamic manipulation, UAV control, among others. Although the practical contexts of these areas appear to be different, the underlying research questions have a lot in common: (1) how to obtain a good dynamic model (rigid-body dynamics, system identification); (2) how to design a controller to achieve a desired dynamic performance (model predictive control, optimal control); (3) how to effectively interact with the environment and other robots (motion planning, reinforcement learning, collision avoidance).

Our lab is directed by Prof. Wei Zhang, and is part of the SUSTech Institute of Robotics, led by Prof. I-Ming Chen and Prof. Yiming Rong.

Research Areas

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