Ruyi Dong

Jilin University of Chemical Technology, Jilin Province Science and Technology Department

Papers

Total Citations

H-Index

About

Ruyi Dong is a researcher advancing intelligent robotic control and spatial reasoning, with key contributions in reinforcement learning and qualitative spatial representation. Their most impactful work, "An enhanced deep deterministic policy gradient algorithm for intelligent control of robotic arms" (2023, 24 citations), addresses the critical challenge of poor robustness and adaptability in traditional robotic control methods. Dong improved the deep deterministic policy gradient (DDPG) algorithm by designing a hybrid reward function that superimposes different reward signals, significantly enhancing the algorithm's performance in dynamic environments. This work has direct implications for autonomous robotic manipulation and adaptive control systems. Additionally, Dong has explored qualitative spatial reasoning in "Qualitative Spatial Reasoning with Oriented Point Relation in 3D Space" (2019, 3 citations), focusing on the Oriented Point Relation Algebra (OPRAm) model. This research provides powerful expressive capabilities for robot navigation under uncertain directional information, offering advantages over traditional point-based spatial models. By bridging reinforcement learning and spatial cognition, Dong’s work contributes to more intelligent and adaptable robotic systems, with potential applications in manufacturing, autonomous navigation, and human-robot interaction.