Run Luo
Papers
2
Total Citations
95
H-Index
2
About
Run Luo is a leading researcher in robotics and optimization, specializing in multi-objective path planning for mobile robots operating in hazardous environments. His work focuses on developing hybrid algorithms that combine ant colony optimization, A* search, and particle swarm optimization to solve complex navigation challenges. Luo's major contributions include pioneering a two-layer cost grid map model that accurately simulates real-world nuclear accident sites, enabling robots to navigate while balancing radiation exposure, distance, and energy efficiency. His 2023 paper on improved ant colony optimization with modified A* has garnered 56 citations, while his hybrid IACO-A*-PSO algorithm has earned 39 citations, reflecting the significant impact of his research on autonomous systems in dangerous settings. Luo's innovative approach to multi-objective path planning has practical implications for disaster response, nuclear decommissioning, and environmental monitoring, making him a key figure in the advancement of intelligent robotics for safety-critical applications.
Research Focus
Key Achievements
Top Papers
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