Xian-Min Wei
Papers
2
Total Citations
13
H-Index
2
About
Xian-Min Wei is a researcher specializing in mobile robotics and intelligent optimization algorithms, with a particular focus on autonomous path planning for mobile robots. Wei's most notable contribution lies in the innovative integration of simulated annealing algorithms with artificial neural networks to address longstanding challenges in global path planning — specifically the computational inefficiencies, excessive iteration demands, and slow convergence rates that have historically limited practical robotic navigation systems. Wei's 2013 work on robot path planning demonstrated a meaningful advance in the field by proposing improved hybrid optimization strategies that better balance exploration and computational efficiency. The research has attracted 13 citations across two related publications, reflecting a focused but meaningful contribution to the robotics and computational intelligence communities. The dual publication of this work — with both a standard and an "efficient" variant — suggests a commitment to iterative refinement and practical applicability of the proposed methods. Wei's research sits at the intersection of bio-inspired computing and robotics engineering, making it relevant to students and practitioners interested in autonomous systems, swarm intelligence, and real-world robotic deployment. While still an emerging body of work, Wei's contributions offer valuable methodological insights for researchers tackling optimization challenges in dynamic environments.
Research Focus
Key Achievements
Top Papers
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- 2