Yi Long

Papers

Total Citations

H-Index

About

Yi Long is a robotics and automation researcher whose work bridges foundational motion planning with practical engineering solutions. His most influential contribution addresses a core challenge in nonholonomic robotics: generating globally feasible trajectories in dynamic environments. In his 2007 paper (34 citations), Long developed a method that breaks complex paths into regional polynomial segments, each incorporating collision avoidance criteria against moving obstacles—a critical advancement for autonomous vehicles and mobile robots operating in unpredictable settings. This work remains relevant for researchers tackling real-time navigation problems. Long also engages with the pressing demands of electric vehicle infrastructure, as seen in his 2019 design of a high-power fully automatic charging device (8 citations). Here, he tackled the practical problem of heavy charging cables by engineering an automated system that reduces user burden while supporting high-current transfer. This dual focus—theoretical rigor in trajectory generation and applied innovation in EV charging—demonstrates Long’s versatility. His research speaks to students and engineers alike: those interested in autonomous navigation will find his polynomial trajectory framework a valuable tool, while those focused on sustainable transportation can learn from his user-centered approach to charging technology.