Xiandong Xu

Harbin Institute of Technology, Heilongjiang Institute of Technology

Papers

Total Citations

H-Index

About

Xiandong Xu is a researcher whose work centers on advancing the autonomous navigation and localization capabilities of humanoid robots. His primary research areas include indoor localization, hybrid mapping, and intelligent path planning for bipedal platforms. Xu’s major contributions lie in developing robust methods to help humanoid robots understand and move through complex indoor environments. He pioneered a hybrid map-based localization approach that combines global topological maps with local metrical maps, enabling robots like the NAO to accurately determine their position using natural and artificial landmarks. To improve navigational efficiency, Xu also introduced a virtual force-directed Particle Swarm Optimization (PSO) algorithm for path planning, which treats obstacles as repulsive forces and targets as attractive forces to guide footstep generation. His work on reducing localization errors through artificial landmark recognition has further enhanced the reliability of humanoid robots in real-world settings. With key papers accumulating citations in the robotics community, Xu’s research provides foundational techniques for creating more autonomous and perceptive humanoid systems, directly contributing to the practical deployment of legged robots in human-centric spaces.