Zhengan Wang

Harbin Engineering University, Zhejiang University of Technology

Papers

Total Citations

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About

Zhengan Wang is a robotics researcher whose work centers on autonomous navigation, path planning, and human-robot interaction. His most influential contribution is the development of the Smooth-RRT algorithm for Autonomous Underwater Vehicles (AUVs), which addresses the critical need for real-time, collision-free path planning in complex underwater environments—a paper that has accumulated 33 citations. Wang has also advanced multi-human pose estimation for real-time human-robot interaction systems, proposing an iterative method for 3D pose capture from multi-view cameras (14 citations). His research further tackles classical path planning challenges, including a fast-convergence ant colony algorithm for mobile robots that overcomes slow convergence and local minima traps (13 citations), and a hybrid algorithm combining gradient-based optimization with A* to reduce path oscillation in cluttered spaces. Wang’s work bridges theoretical optimization and practical robotic deployment, with applications ranging from underwater exploration to collaborative robotics. His contributions are particularly notable for improving the efficiency and robustness of autonomous navigation, making him a key figure in the field of intelligent robotics and motion planning.