Yinchu Wang

Northwest A&F University, Jilin Medical University, Beijing University of Chemical Technology

Papers

Total Citations

121

H-Index

About

Yinchu Wang is a leading researcher in agricultural robotics and autonomous navigation, with a primary focus on intelligent path planning for complex environments. His most impactful work, "Coverage path planning for kiwifruit picking robots based on deep reinforcement learning" (2022, 103 citations), represents a significant breakthrough in precision agriculture. This research pioneered the application of deep reinforcement learning to enable kiwifruit harvesting robots to efficiently navigate orchards, optimizing coverage while minimizing redundant movement—a critical advancement for reducing harvest time and fruit damage. Wang’s broader contributions address persistent challenges in mobile robotics, including local deadlock and path redundancy in unknown environments, as detailed in his 2021 study on path planning algorithms (15 citations). His recent work on inspection robots for large storage tank bottoms (2023) further demonstrates his versatility, tackling the dual problems of local minima entrapment and path smoothness in confined industrial settings. With over 120 total citations, Wang’s research bridges the gap between theoretical reinforcement learning and practical robotic deployment, offering scalable solutions for both agricultural automation and industrial inspection. His innovative use of deep learning for coverage path planning has established him as a key figure in the evolution of intelligent, adaptive robotic systems.