Xia Shen

Wuhan University of Science and Technology

Papers

Total Citations

H-Index

About

Xia Shen is a robotics researcher whose work focuses on advancing autonomous navigation and perception for mobile robots. His key research areas include path planning, obstacle avoidance, and 3D simultaneous localization and mapping (SLAM), with a particular emphasis on real-time performance and bio-inspired algorithms. Shen’s most cited paper, “Path planning of mobile robot by mixing experience with modified artificial potential field method” (2015, 33 citations), introduces a novel approach that integrates case-based reasoning with a modified artificial potential field method. This work enables mobile robots to effectively avoid collisions by leveraging past experiences during global obstacle avoidance, significantly improving adaptability in dynamic environments. In another notable contribution, “Fast RGBD-ICP with bionic vision depth perception model” (2015), Shen addresses a critical challenge in 3D SLAM—enhancing real-time performance. By modeling depth perception after biological vision systems, his method optimizes RGBD sensor data processing, paving the way for faster and more efficient robot mapping. Shen’s research demonstrates a creative fusion of robotics, computer vision, and bionics, offering practical solutions for autonomous systems. His work is particularly valuable for students and engineers interested in developing smarter, more responsive mobile robots for real-world applications.