Papers
1
Total Citations
9
H-Index
1
About
Mandan Chao is a robotics researcher whose work focuses on the control and planning of agile, wheeled-bipedal robots—machines that combine the mobility of wheels with the dynamic capabilities of legged locomotion. In his highly cited 2021 paper, "Height Control and Optimal Torque Planning for Jumping With Wheeled-Bipedal Robots," Chao tackles the formidable challenge of enabling these underactuated systems to perform precise, energy-efficient jumps. His major contribution lies in developing a torque planning framework that optimizes energy consumption while achieving accurate height control, addressing critical issues such as nonlinear estimation and the instantaneous impacts inherent in jumping maneuvers. This work has garnered 9 citations, marking it as a foundational reference for researchers exploring dynamic locomotion in hybrid robotic platforms. Chao’s research is particularly notable for bridging the gap between theoretical control strategies and practical, real-world robotic agility, offering a pathway toward more versatile and resilient robots capable of navigating complex, unstructured environments. His achievements underscore a commitment to advancing the frontiers of robot motion planning and control.
Research Focus
Key Achievements
Top Papers
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