Papers
53
Total Citations
817
H-Index
15
About
Jingchuan Wang is a robotics researcher whose work spans soft robotics, visual servoing, mobile robot navigation, and multi-robot coordination — areas where intelligent perception and control intersect with real-world deployment challenges. His most influential contribution, "Underwater Dynamic Visual Servoing for a Soft Robot Arm With Online Distortion Correction" (2019, 71 citations), pioneered vision-based control for bioinspired soft robots operating in demanding underwater environments, addressing the formidable modeling challenges their unconventional mechanics present. Complementing this, his work on hybrid vision/force control and adaptive visual servoing of contour features has meaningfully advanced the field of precision robotic manipulation. Wang has also made notable strides in multi-robot systems, developing distributed formation control strategies that account for real-world communication delays and sampled-data constraints, as well as trajectory coordination algorithms for fleets of automated guided vehicles in warehouse environments. His contributions to long-term visual SLAM using Bayesian persistence filtering reflect a growing emphasis on robust localization under changing conditions, while earlier work on probabilistic localizability estimation demonstrates a sustained commitment to foundational mobile robotics problems. With over 460 cumulative citations, Wang's research consistently bridges theoretical rigor with practical, deployable robotic systems.
Research Focus
Key Achievements
Top Papers
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- 3Adaptive Visual Servoing of Contour Features63 citations · 2018
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- 5Hybrid Vision/Force Control of Soft Robot Based on a Deformation Model50 citations · 2019
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- 9Automatic illumination planning for robot vision inspection system28 citations · 2017
- 10Active global localization based on localizability for mobile robots21 citations · 2014