Papers
18
Total Citations
347
H-Index
11
About
Chuxiong Hu is a versatile researcher whose work spans robotics, motion control, energy systems, and biomedical engineering, establishing him as a significant interdisciplinary voice in modern engineering science. His most impactful contribution to date is his 2023 study on hybrid energy storage systems and management strategies for high-torque motor drives, which has garnered an impressive 72 citations in a short time, reflecting the urgency and relevance of intelligent energy management in advanced drive systems. Hu has made foundational contributions to trajectory planning, developing both time-optimal control frameworks for constrained multi-axis systems and real-time local greedy search algorithms — work that directly benefits robotics, CNC manufacturing, and autonomous vehicles. His research on CPG-based locomotion control for modular quadrupedal robots using deep reinforcement learning demonstrates a sophisticated command of bio-inspired and learning-based control architectures. Notably, Hu's research extends into cutting-edge biomedical territory, including laser-direct-write sensors for smart orthopedic implants and robot-assisted subaqueous bioprinting for fetal membrane repair — areas with profound clinical implications. With over 290 citations across his top works and contributions ranging from industrial manipulation to surgical robotics, Hu represents a rare breadth of rigorous, high-impact engineering scholarship.
Research Focus
Key Achievements
Top Papers
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- 9Real-Time Local Greedy Search for Multiaxis Globally Time-Optimal Trajectory16 citations · 2023
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