Xiaoming Kang

Beijing Institute of Architectural Design (China)

Papers

Total Citations

H-Index

About

Xiaoming Kang is a robotics researcher whose work focuses on intelligent navigation and path planning for mobile robots operating in complex, obstacle-rich environments. His most significant contribution addresses the critical "dead-end problem"—situations where a robot becomes trapped in areas surrounded by obstacles. While previous approaches aimed to avoid dead-ends entirely, Kang’s 2011 paper proposed a novel genetic algorithm-based solution that enables robots to deliberately enter and then successfully escape from dead-end zones. This is particularly vital for applications like search and rescue, where exploring every accessible area, including potential traps, is essential. His work has garnered over 26 citations, reflecting its practical importance in advancing autonomous navigation beyond simple obstacle avoidance. By reframing dead-ends as navigable challenges rather than impassable barriers, Kang has helped push the boundaries of robotic autonomy in unstructured, real-world environments, making his research a key reference for engineers developing resilient exploration algorithms.