Associate Professor Department of Mechanical and Energy Engineering

Prof. Chenglong Fu obtained his B.S. from the Department of Mechanical Engineering, Tongji University in 2002 and Ph.D. from the Department of Precision Instruments and Mechanology, Tsinghua University, in 2007. His research interests include dynamic walking, biped and humanoid robots, powered prosthesis, lower limb exoskeleton and human robot interaction. He is the principle investigator of more than 20 research projects, including 4 NSFC, 2 National Key R&D Program of China and 8 national defense projects. He has published more than 80 papers and 2 academic monographs, the most cited paper of him has been cited for more than 130 times, and he holds more than 30 granted patents. He is an Associate Editor and Workshop Co-Chair of IEEE-RAS Humanoids 2018 and 2019, and co-organizer in IROS 2019 Workshop (Supernumerary Robotic Limbs). He received the Best Student Paper Award Finalist, IEEE International Conference on Advanced Robotics and its Social Impacts (ARSO), 2019.

Walking is a basic human activity which deserves scientific understanding. My research focuses on the predictive principles underlying dynamic walking of humans and robots. These principles are important not only for robotics, but also for rehabilitation and human movement science. In 2016, I set up the Human-Augmented Robotics Lab (HARL) in SUSTech. Research topics of the HARL include predictive walking principles, powered prosthesis, lower-limb exoskeleton, suspended backpack, and super limbs.

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Dynamic walking, biped and humanoid robots, robotic prosthesis, lower limb exoskeleton and human robot interaction

Publications Read More

[1] Yang L, Zhang J, Xu Y, Chen K, Fu C*. Energy Performance Analysis of a Suspended Backpack with an Optimally Controlled Variable Damper for Human Load Carriage. Mechanism and Machine Theory 146 (2020) 103738. (Published online at DOI: 10.1016/j.mechmachtheory.2019.103738)

[2] Zhang K, Wang J, de Sliva C W, Fu C*, Unsupervised Cross-subject Adaptation for Predicting Human Locomotion Intent. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2020. (Accepted, in press).

[3] Hao M, Chen K, Fu C*. Smoother-based 3D Foot Trajectory Estimation Using Inertial Sensors. IEEE Transactions on Biomedical Engineering. 66(12): 3534-3542, 2019.

[4] Zhang K, Xiong C, Zhang W, Liu H, Lai D, Rong Y, Fu C*. Environmental Features Recognition for Lower Limb Prostheses Toward Predictive Walking. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27(3): 465-476, 2019.

[5] Zhang K, Zhang W, Xiao W, Liu H, de Silva C W, Fu C*. Sequential Decision Fusion for Environmental Classification in Assistive Walking. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 27(9): 1780-1790, 2019.

[6] Liu J, Xiong C, Fu C*. An Ankle Exoskeleton Using Lightweight Motor to Create High Power Assistance for Push-off. ASME Journal of Mechanisms and Robotics. 11(4): 041001-041001-10. 2019.

[7] Hao M, Chen K, Fu C*. Effects of Hip Torque during Step-to-step Transition on Center-of-Mass Dynamics during Human Walking Examined with Numerical Simulation. Journal of Biomechanics, 90: 33-39, 2019.

[8] Chang Y, Wang W, Fu C*. A Lower Limb Exoskeleton Recycling Energy from Knee Joint and Ankle Joint to Assist Push-off. ASME Journal of Mechanisms and Robotics, 2019. (accepted, in press)

[9] Wu Z, Zhang J, Chen K, Fu C*. Yoga Posture Recognition and Quantitative Evaluation with Wearable Sensors Based on Two-stage Classifier and Prior Bayesian Network. Sensors, 19(23), 5129; doi:10.3390/s19235129, 2019.

[10] Luo J, Su Y, Ruan L, Zhao Y, Kim D, Sentis L, Fu C*. Robust Bipedal Locomotion Based on a Hierarchical Control Structure. Robotica. 37(10): 1750-1767, 2019.

[11] Qin M, Yu Z, Chen X, Meng L, Huang Q, Fu C. Computationally Efficient Coordinate Transformation for Field-Oriented Control Using Phase Shift of Linear Hall-Effect Sensor Signals. IEEE Transactions on Industrial Electronics. doi:10.1109/TIE.2019.2922920, 2019.

[12] Zhang L, Fu C*. Predicting Foot Placement for Balance through a Simple Model with Swing Leg Dynamics. Journal of Biomechanics, 77: 155-162, 2018.

[13] Wu Y, Wu Z, Fu C*. Continuous Arm Gesture Recognition Based on Natural Features and Logistic Regression. IEEE Sensors Journal, 18(19): 8143-8153, 2018.

[14] Gao W, Jia Z, Fu C*. Increase the Feasible Step Region of Biped Robots through Active Vertical Flexion and Extension Motions. Robotica, 35(7): 1541-1561, 2017.

[15] Wu Y, Chen K, Fu C*. Effects of Load Connection Form on Efficiency and Kinetics of Biped Walking. ASME Journal of Mechanisms and Robotics, 8(6): 061015-061015-10, 2016.

[16] Wu Y, Chen K, Fu C*. Natural Gesture Modeling and Recognition Approach Based on Joint Movements and Arm Orientations. IEEE Sensors Journal, 16(21): 7753-7761, 2016.

[17] Fu C*, Wang J, Chen K, Yu Z, Huang Q. A Walking Control Strategy Combining Global Sensory Reflex and Leg Synchronization. Robotica, 34(5): 973-994, 2016.

[18] Fu C*, Tan F, Chen K. A Simple Walking Strategy for Biped Walking Based on an Intermittent Sinusoidal Oscillator. Robotica, 28(6): 869-884, 2010.

[19] Fu C*, Chen K. Gait Synthesis and Sensory Control of Stair-climbing for a Humanoid Robot. IEEE Transactions on Industrial Electronics, 55(5): 2111-2120, 2008.

[20] Tan F, Fu C*, Chen K. Biped Blind Walking on Changing Slope with Reflex Control System. IEEE International Conference on Robotics and Automation (ICRA). Anchorage, Alaska, USA. May 2010. 1709-1714.

[21] Fu C*. Perturbation Recovery of Biped Walking by Updating the Footstep. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Chicago, USA. September 2014. 2509-2514.

[22] Fu C*, Shuai M, Huang Y, Wang J, Chen K. Parametric Walking Patterns and Optimum Atlases for Underactuated Biped Robots. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Beijing, China. October 2006. 342-347.

[23] Chen K, Fu C. Theory and Technology of Humanoid Robots. June 2010. Tsinghua University Press, Beijing, China. (ISBN 978-7-302-22544-7)

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