Tielong Tan
Papers
2
Total Citations
63
H-Index
2
About
Dr. Tielong Tan is a leading researcher in mobile robotics, specializing in intelligent path planning and navigation algorithms. His work centers on developing hybrid optimization techniques that overcome the limitations of traditional single-algorithm approaches. Dr. Tan’s most influential contribution is the integration of the improved mayfly optimization algorithm with the dynamic window approach for mobile robot path planning, a method that has garnered 53 citations for its effectiveness in balancing global route optimization with real-time obstacle avoidance. He further advanced the field by fusing ant colony optimization with genetic algorithms, addressing critical shortcomings such as redundant nodes and slow convergence through a novel “selection-crossover” mechanism. This fusion algorithm, published in 2023, demonstrates his commitment to enhancing computational efficiency and path quality in complex environments. Dr. Tan’s work has been widely recognized for its practical applicability in autonomous navigation systems, making significant strides in improving robot autonomy and operational reliability. His research continues to inspire new approaches in swarm intelligence and multi-algorithm fusion for robotics.
Research Focus
Key Achievements
Top Papers
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