Papers
7
Total Citations
98
H-Index
5
About
Juntong Su is a leading researcher in robotics, specializing in quadruped locomotion, robotic machining, and adaptive control systems. His work bridges the gap between dynamic legged robots and precision manufacturing, with a focus on payload capacity and environmental adaptability. Su’s major contributions include developing unknown payload adaptive control for quadruped robots using proprioceptive linear legs, enabling stable locomotion under severe disturbances—a breakthrough for real-world applications like rescue and exploration. His design of prismatic quasi-direct-drives has significantly enhanced payload capacity in dynamic quadruped locomotion, while his sparse Bayesian learning model for in-situ foreknowledge of robotic machining errors has improved precision in manufacturing. Su’s self-adaptive agent for flexible posture planning in robotic milling systems, along with his divide-and-conquer strategy for constrained milling on curved surfaces, demonstrates his innovative approach to complex robotic tasks. With over 98 citations across his top papers, Su’s work is highly influential, particularly his 2022 study on quadruped adaptive control (29 citations) and his large-scale electrically-actuated quadruped robot design for narrow passages (11 citations). His recent digital twin system for robotic milling further showcases his commitment to advancing service-expansion in manufacturing. Su’s research is essential reading for students and engineers interested in robust, high-payload robotic systems and intelligent machining.
Research Focus
Key Achievements
Top Papers
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