Xiaogang Tang

Papers

Total Citations

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About

Xiaogang Tang is a researcher focused on advancing autonomous robot navigation and control, with particular expertise in path planning and tracking control for wheeled mobile robots. His work addresses critical challenges in dynamic, real-world environments, moving beyond traditional static obstacle assumptions. Tang’s most-cited paper, "Hybrid Path Planning Algorithm Based on Improved Dynamic Window Approach" (2021, 6 citations), introduces a novel hybrid algorithm that enhances the Dynamic Window Approach for dynamic settings, significantly improving real-time obstacle avoidance and path efficiency. In his related work, "Tracking Control of Wheeled Mobile Robot Based on RBF Network Supervisory Control" (2020, 2 citations), he tackles the persistent issue of precise trajectory tracking under nonholonomic constraints, leveraging Radial Basis Function networks for adaptive supervisory control. While his citation counts reflect an emerging career, Tang’s contributions are notable for their practical focus on overcoming the limitations of conventional models, offering scalable solutions for industrial, agricultural, and defense applications. His research bridges theoretical control methods with real-world deployment, making him a promising voice in the field of mobile robotics and autonomous systems.