Maowei He
Papers
3
Total Citations
7
H-Index
2
About
Dr. Maowei He is a researcher at the forefront of intelligent robotics and meta-heuristic optimization, with a particular focus on mobile robot path planning and global optimization algorithms. His work bridges the gap between nature-inspired computing and practical engineering applications, addressing critical challenges in autonomous navigation and complex problem-solving. He has made significant contributions by developing hybrid algorithms that enhance the efficiency and adaptability of robotic systems. Notably, his 2025 paper on an improved ant colony Q-learning algorithm for path planning has already garnered 3 citations, reflecting its immediate impact. His earlier work on an adaptive bacterial foraging algorithm (2016) and an orthogonal learning-based improved slime mould algorithm (2021) each hold 2 citations, demonstrating sustained interest in his innovative approaches. These meta-heuristic algorithms are widely applied in production scheduling, robot path optimization, and mechanical design, showcasing the practical relevance of his research. Dr. He’s ability to integrate learning mechanisms with swarm intelligence positions him as a rising voice in optimization-driven robotics.
Research Focus
Key Achievements
Top Papers
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