Maojia Li

Papers

Total Citations

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About

Maojia Li is a researcher focused on advancing autonomous navigation and intelligent material handling systems, with a particular emphasis on mobile robotics in industrial environments. Their most cited work, "Turn and Orientation Sensitive A* for Autonomous Vehicles in Intelligent Material Handling Systems" (2020), introduces a dynamic path planning algorithm that adapts the classic A* search method for large autonomous vehicles like forklifts. This contribution addresses critical challenges in warehouse automation, where efficient and safe navigation can reduce accidents and improve operational throughput. With 4 citations, this paper highlights Li’s early impact in a field where practical, safety-oriented solutions are urgently needed. Li’s research sits at the intersection of robotics, logistics, and artificial intelligence, aiming to make autonomous systems more responsive to real-world constraints such as vehicle orientation and turning radii. Their work is particularly relevant for students and researchers interested in applied path planning, industrial automation, and the integration of intelligent systems into material handling. Li’s contributions offer a promising foundation for safer, more efficient warehouses and factories.