Juan Liu

Papers

Total Citations

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About

Juan Liu is a robotics and autonomous systems researcher whose work has made meaningful contributions to mobile robot navigation and intelligent control. Her most recognized contribution centers on enhancing the dynamic window approach (DWA) for obstacle avoidance in mobile robots — a foundational challenge in autonomous navigation. Published in 2017 and accumulating 46 citations, her improved DWA framework addresses critical limitations of the conventional method, particularly its susceptibility to local minima and suboptimal motion decisions. By incorporating the physical size constraints of mobile robots into the decision-making process, Liu's approach yields more reliable and geometrically aware navigation strategies, advancing the practical deployment of autonomous ground robots in complex environments. Her research sits at the intersection of motion planning, real-time decision-making, and robotic safety — areas of growing importance as autonomous systems become increasingly prevalent in industrial, service, and research settings. Liu's work demonstrates a strong focus on bridging theoretical algorithmic improvements with real-world applicability, making her contributions particularly valuable to both academic researchers and engineers developing next-generation robotic platforms. Her citation record reflects a growing recognition of her practical and technical insights within the robotics community.