Jiangping Wang

Hangzhou Dianzi University, Zhejiang Lab

Papers

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About

Jiangping Wang is a robotics researcher specializing in motion planning, visual servoing, and human-robot interaction. Their most impactful contribution is the development of an inverse kinematics-based motion planning algorithm for dual-arm robots with orientation constraints, which combines sampling-based planning with analytical inverse kinematics to achieve efficient, probabilistically complete solutions (19 citations). This work addresses critical challenges in decoupled dual-arm systems, enabling more dexterous and constrained manipulation tasks. Wang also advanced person-following capabilities for service robots by integrating Haar-like features with Histogram of Oriented Gradients (HOG) and AdaBoost cascade detection, enhancing indoor autonomous navigation (3 citations). More recently, they proposed a Jacobian estimation method using an adaptive Kalman filter for uncalibrated visual servoing, improving robot control accuracy without prior calibration (3 citations). Wang’s research bridges theoretical planning algorithms with practical robotic applications, contributing to safer and more adaptive human-robot collaboration. Their work is particularly relevant for students and researchers interested in dual-arm coordination, visual servoing, and assistive robotics.