Xianglong Lu

Papers

Total Citations

H-Index

About

Xianglong Lu is a researcher at the forefront of intelligent vehicle systems and multi-robot coordination, with a focus on making autonomous ground vehicles both practical and affordable. His work centers on the ambitious FAME (Flexible Autonomous Machines operating in an uncertain Environment) framework, where he addresses critical challenges in modeling, design, and control. Lu’s major contributions include pioneering the development of low-cost differential-drive robotic platforms, demonstrating that sophisticated autonomous capabilities can be achieved without prohibitive expense. His two-part study on these vehicles (2017) systematically tackles single-vehicle dynamics and extends to multi-vehicle cooperation, laying essential groundwork for fleet coordination in uncertain environments. Additionally, his work on "VC-bots" (2016, 23 citations) explores how smart vehicles equipped with computing, sensing, and communication can revolutionize traffic optimization, data collection, and safety. While his citation counts reflect a focused, emerging impact, Lu’s research is notable for its practical engineering approach—bridging theoretical control with real-world deployability. His contributions are particularly valuable for students and researchers interested in accessible robotics, intelligent transportation, and the scalable deployment of autonomous ground vehicle fleets.