Minghai Jiao
Papers
5
Total Citations
22
H-Index
4
About
Minghai Jiao is a researcher whose work bridges robotics, optimization algorithms, and artificial intelligence, with a primary focus on mobile robot path planning. His major contributions lie in enhancing autonomous navigation through the application and improvement of reinforcement learning, ant colony optimization, and quantum particle swarm optimization. Notably, his 2019 paper on "Mobile Robot Path Planning Based on Improved Reinforcement Learning Optimization" and his 2020 work on ant colony optimization each garnered 6 citations, demonstrating early impact in addressing NP-hard path planning challenges for service robots, including those designed for elderly care. Jiao’s research introduces novel models that transform complex community environments into grid-based mathematical representations, enabling more efficient and locally optimal solutions. His 2018 study on quantum particle swarm optimization for aged-service robots further underscores his commitment to practical, socially beneficial applications. More recently, Jiao has expanded into computer vision with "Pixel2Noise" (2025), a lightweight self-supervised denoising method for single-image zero-shot recognition, showcasing versatility. With a cumulative citation count reflecting steady influence, Jiao’s work is a valuable resource for students and researchers exploring optimization-driven robotics and AI.
Research Focus
Key Achievements
Top Papers
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