Papers
3
Total Citations
23
H-Index
2
About
Zengwei Wang is a robotics researcher whose work centers on advancing human-robot interaction, precision tracking, and soft robotic manipulation. His key contributions span three critical areas: multi-sensor fusion for robust pose estimation, control strategies for natural human-robot companionship, and the design of flexible continuum robots. Wang’s 2021 paper on 6-D pose tracking, which fuses a multi-camera system with an AHRS module to overcome line-of-sight limitations, has garnered 16 citations and addresses a fundamental challenge in robot and VR tracking. His 2024 work introduces an LQR-based control strategy that enhances a companion robot’s ability to navigate dynamic, unstructured environments while maintaining natural interaction with humans—a vital step toward seamless human-robot symbiosis. Most recently, Wang has pioneered the design of a 3D-printed, tendon-driven continuum robot featuring spring-based flexure joints, demonstrating how additive manufacturing can enable complex, compliant structures for minimally invasive surgery. By integrating optical tracking, intelligent control, and soft robotics, Wang is building the foundational technologies for robots that can perceive, accompany, and safely interact with humans in real-world settings.
Research Focus
Key Achievements
Top Papers
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