Shuhao Jiang

Papers

Total Citations

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About

Shuhao Jiang is a leading researcher in autonomous navigation and rescue robotics, with a focus on improving mapping accuracy and navigation efficiency in complex, unknown environments. His major contributions center on advancing simultaneous localization and mapping (SLAM) algorithms for rescue robots, where he has developed innovative solutions to overcome challenges such as sparse environmental features and high-speed operation. Jiang’s most cited work, "An Autonomous Navigation Strategy Based on Improved Hector SLAM With Dynamic Weighted A* Algorithm" (2023, 13 citations), introduces a novel approach that integrates Levenberg-Marquardt optimization with Bezier smooth dynamic weighting to enhance path planning and mapping precision. His second highly cited paper, "An improved bicubic interpolation SLAM algorithm based on multi-sensor fusion method for rescue robot" (2023, 6 citations), tackles the problem of accurate map construction by fusing multi-sensor data with bicubic interpolation techniques. These works demonstrate Jiang’s ability to push the boundaries of rescue robot autonomy, offering practical solutions for real-world disaster response scenarios. His research continues to inspire advancements in robotic navigation, making him a notable figure in the field of autonomous systems.