Shunxiang Wu

Xiamen University of Technology, Xiamen University

Papers

Total Citations

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About

Shunxiang Wu is a pioneering researcher in autonomous robotics, with a primary focus on intelligent path planning and multi-sensor fusion for mobile robots operating in unknown environments. His most influential work, "Ant colony optimization with potential field heuristic for robot path planning" (2010, 14 citations), introduces the ACOPF algorithm—a novel hybrid that combines ant colony optimization with artificial potential fields. By integrating potential field resultant forces and goal-distance metrics into the heuristic, Wu’s approach enables robots to navigate complex, uncharted spaces with remarkable efficiency, offering a significant advance over traditional methods. In his equally impactful 2009 study (10 citations), Wu designed a composite ultrasonic and infrared sensor array and developed a groundbreaking multi-sensor information fusion technique using BP neural networks and fuzzy control. This work dramatically expanded robot detection ranges and decision-making accuracy. Together, these contributions have established Wu as a key innovator in bio-inspired robotics and sensor integration, laying critical groundwork for autonomous navigation systems in real-world applications.