Chaoyi Dong

Inner Mongolia University of Technology, Mongolian University of Science and Technology

Papers

Total Citations

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About

Chaoyi Dong’s research focuses on advancing autonomous navigation for mobile robots and automated guided vehicles (AGVs), with particular emphasis on path planning, simultaneous localization and mapping (SLAM), and sensor-based perception. His most impactful work, an improved A* algorithm for mobile robot path planning, has garnered 19 citations and addresses the critical challenge of generating optimal paths in static environments by refining heuristic functions. Dong also tackles the computational inefficiencies of traditional particle filter SLAM, proposing an improved particle filter (IPF-SLAM) algorithm that enhances real-time performance and positioning accuracy for AGVs. In a third notable study, he integrates vision sensors with an enhanced ORB-SLAM2 algorithm to enable robots to autonomously construct maps and navigate unknown environments, directly improving obstacle avoidance and path planning capabilities. Collectively, Dong’s contributions—spanning algorithm optimization, sensor fusion, and real-world deployment—have laid a strong foundation for more efficient and reliable autonomous systems. His work is particularly relevant for researchers and engineers developing intelligent logistics, warehouse automation, and field robotics.