Papers
6
Total Citations
341
H-Index
5
About
Zhiqiang Lin is a multidisciplinary robotics and materials researcher whose work bridges advanced sensing technologies, soft robotics, and intelligent autonomous systems. His most impactful contributions lie in the development of highly stretchable and sensitive strain sensors, where he has tackled one of the field's most persistent challenges: the fundamental trade-off between stretchability and sensitivity. His 2018 paper on gradient-structure carbon nanotube strain sensors (98 citations) and his 2020 work on synergistic hybrid conductive networks (61 citations) represent significant breakthroughs in wearable electronics and human motion detection. Lin has also made notable strides in soft robotics, with his accordion-inspired pneumatic actuators for knee assistive devices (77 citations) offering a compelling solution to comfort, torque output, and cost barriers in rehabilitation technology. In parallel, his research in robot intelligence is well recognized, particularly his fuzzy Bayesian reinforcement learning approach to robotic soccer decision-making (60 citations), demonstrating a sophisticated command of adaptive autonomous systems. More recently, his work on binocular vision-based obstacle avoidance for substation inspection robots signals a broadening focus toward real-world industrial deployment. Collectively, Lin's publications reflect a researcher equally comfortable at the intersection of materials science, biomechanics, and machine intelligence.
Research Focus
Key Achievements
Top Papers
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