Yanshu Jing
Papers
2
Total Citations
12
H-Index
2
About
Yanshu Jing is a researcher specializing in autonomous mobile robotics, with a primary focus on path planning and optimization algorithms. Their work bridges classical bio-inspired techniques and modern reinforcement learning to enhance robot navigation in complex environments. Jing’s most cited papers, each garnering 6 citations, address critical limitations in traditional path planning methods. In “Mobile Robot Path Planning Based on Improved Reinforcement Learning Optimization” (2019), they refined Q-learning by eliminating constant parameter settings in adaptive functions, significantly boosting learning efficiency for autonomous navigation. Their 2020 paper, “Mobile Robot Path Planning Based on Improved Ant Colony Optimization Algorithm,” further advanced the field by enhancing the ant colony algorithm’s performance, demonstrating its potential to solve intricate planning problems. Together, these contributions showcase Jing’s ability to synergize reinforcement learning with bionic optimization, offering more robust and adaptive solutions for mobile robots. Their work is particularly valuable for researchers and students exploring intelligent control systems, as it provides practical improvements to foundational algorithms, paving the way for more responsive and efficient autonomous systems in real-world applications.
Research Focus
Key Achievements
Top Papers
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- 2