LeRong Ma

Tianjin University of Technology and Education

Papers

Total Citations

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About

LeRong Ma is a researcher whose work focuses on advancing mobile robot path planning through computational intelligence. Their most notable contribution is the development of an improved genetic algorithm (IGA) that addresses critical limitations in traditional simple genetic algorithms (SGA) for autonomous navigation. Ma's 2023 paper tackles three persistent challenges in robotic path planning: insufficient path smoothness, susceptibility to local optima, and algorithm instability. By introducing an intermediate value insertion strategy, their IGA approach enhances both the quality and reliability of generated paths, making it particularly valuable for real-world autonomous systems. While still early in its citation impact with 4 citations to date, this work represents a meaningful step forward in applying evolutionary computation to robotics. Ma's research sits at the intersection of artificial intelligence, optimization algorithms, and autonomous systems, offering practical solutions for improving how mobile robots navigate complex environments. Their contributions are especially relevant for researchers and engineers working on autonomous vehicles, warehouse robots, and service robots that require efficient and stable path planning capabilities.