Jiaming Guo

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About

Jiaming Guo is a researcher specializing in robotics, autonomous navigation, and multi-objective optimization, with a particular focus on mobile robot path planning in complex industrial environments. His most cited work addresses the critical challenge of energy-aware multi-objective path planning for warehouse inspection robots, where he developed a two-level solution combining local path planning with an improved algorithm to optimize routes under battery constraints and multiple charging points. This contribution is especially valuable for large-scale logistics and manufacturing facilities seeking to deploy autonomous inspection systems efficiently. With a growing citation record, Guo’s research demonstrates practical impact in bridging theoretical optimization methods with real-world robotic applications. His work on power-limited mobile robots has implications for sustainable automation, reducing downtime and improving operational reliability in warehouses. Guo’s achievements highlight his ability to tackle pressing engineering problems at the intersection of robotics, energy management, and algorithmic design, making his research a key reference for students and professionals developing next-generation autonomous systems.