Hongxiang Jing

Papers

Total Citations

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About

Hongxiang Jing is a robotics researcher whose work centers on the dynamic performance and intelligent control of parallel robotic systems, with a particular focus on high-speed pick-and-place and precision polishing applications. His most impactful contribution to date is the development of an optimal time–jerk trajectory planning method for Delta parallel robots, published in 2022 and garnering 24 citations. In this work, Jing introduced a multi-objective integrated trajectory planning approach based on an improved butterfly optimization algorithm (IBOA), designed to enhance the dynamic behavior of robots during rapid pick-and-place operations—a critical challenge in industrial automation. Additionally, Jing has contributed to the field of precision manufacturing through his research on dynamic modeling and sliding mode control for 3-RSS coaxial layout polishing robots, demonstrating his versatility in addressing both motion efficiency and surface finishing quality. His work bridges optimization theory and practical robotic control, offering tangible improvements in speed, smoothness, and accuracy. With a growing citation footprint, Jing is establishing himself as a promising voice in parallel robotics and mechatronic systems, particularly for applications demanding both speed and precision.