Papers
6
Total Citations
48
H-Index
4
About
Yali Wang is a robotics researcher whose work spans human-machine interaction, state estimation, and intelligent robotic systems. His most cited paper, "Wheeled robot control based on gesture recognition using the Kinect sensor" (2013, 19 citations), addresses a critical challenge in service robotics—moving beyond traditional input devices to enable intuitive, vision-based gesture control. Wang further advanced estimation techniques with "An adaptive nonparametric particle filter for state estimation" (2012, 11 citations), improving upon conventional particle filters by optimizing proposal distributions for more accurate state estimation in practical applications. His contributions to industrial robotics include a novel method for calibrating robot visual measurement systems using laser trackers (2013, 9 citations) and an optimized trajectory planning algorithm (2012, 4 citations) that normalizes velocity and time for efficient manipulator control. Wang also designed an underactuated robotic hand with three articulated fingers (2018, 3 citations), featuring eight degrees of freedom and real-time reconfiguration for grasping diverse objects. More recently, he has explored deep learning for autonomous systems, implementing an improved YOLOv3-Tiny pedestrian detection algorithm within the ROS framework (2022, 2 citations) to enhance detection of small or occluded pedestrians. Wang’s work demonstrates a sustained commitment to making robots more responsive, precise, and capable in real-world environments.
Research Focus
Key Achievements
Top Papers
- 1Wheeled robot control based on gesture recognition using the Kinect sensor19 citations · 2013
- 2An adaptive nonparametric particle filter for state estimation11 citations · 2012
- 3A New Method to Calibrate Robot Visual Measurement System9 citations · 2013
- 4Optimized tracjectory planning algorithm for industrial robot4 citations · 2012
- 5Design of a Underactuated Robotic Hand with Three Articulated Fingers3 citations · 2018
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