Yonglin Jing

Southern University of Science and Technology

Papers

Total Citations

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About

Yonglin Jing is a robotics researcher whose work bridges bio-inspired design and sensor fusion, with a focus on enhancing robotic performance in challenging environments. His key research areas include soft robotics, bio-inspired manipulation, and multi-sensor calibration for autonomous systems. Jing’s major contributions lie in drawing inspiration from rigid-bodied animals—specifically the Boston Lobster—to design soft robotic fingers with enhanced grasping capabilities underwater. His 2021 paper on lobster-inspired finger surfaces (13 citations) introduced a novel rigid-soft interactive design that improves grip robustness in aquatic settings, a domain where soft robots often struggle. He further refined this concept in a subsequent study (3 citations), demonstrating how tooth-like profiles from lobster claws can boost object manipulation under sediment-rich conditions. Beyond bio-inspired design, Jing has advanced sensor fusion with his 2023 work on online calibration between cameras and LiDAR (6 citations), using spatial-temporal photometric consistency to ensure accurate data integration—critical for autonomous navigation. His interdisciplinary approach, combining biological principles with practical robotics challenges, has been recognized for its innovation in underwater grasping and sensor reliability. With a growing citation impact, Jing’s work offers valuable insights for researchers in soft robotics, marine exploration, and autonomous systems.