Jinming Zhang

Zhejiang Gongshang University, University of Science and Technology of China

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About

Jinming Zhang is a robotics researcher whose work centers on intelligent navigation, mapping, and path planning for mobile robots. His key contributions lie in developing novel representations and algorithms that enable robots to operate more effectively in complex, real-world environments. Zhang’s most impactful work, “An Occupancy Information Grid Model for Path Planning of Intelligent Robots” (2022, 21 citations), advances beyond traditional occupancy grids by integrating richer information, directly improving a robot’s ability to make smarter navigation decisions. He has also tackled persistent challenges in indoor mapping, proposing an adaptive pose fusion method (2021) that significantly enhances pose estimation accuracy and map detail in difficult conditions like poor lighting or dynamic spaces. Most recently, his 2025 paper addresses the practical problem of energy management in large-scale warehouses, introducing a multi-objective path planning approach that accounts for battery limits and multiple charging points. Through these contributions, Zhang is helping to bridge the gap between theoretical robotics and practical, deployable systems, making autonomous robots more reliable and efficient for tasks ranging from inspection to logistics.