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About

Yanyan Lu is a researcher in robotics and motion planning, with a focus on developing efficient algorithms for navigating robots through complex, dynamic environments. Her work addresses the fundamental challenge of reusing computational solutions across similar problems, as demonstrated in her most-cited paper, "Planning motion in environments with similar obstacles" (2009, 37 citations). This research explores how motion plans for one environment can be adapted to solve new, structurally similar problems, offering significant practical applications in fields like manufacturing and autonomous navigation. Lu has also made notable contributions to collision prediction, particularly for obstacles with arbitrary shapes and unknown motion. Her papers "Online collision prediction among 2D polygonal and articulated obstacles" (2015, 6 citations) and "Collision prediction among polygons with arbitrary shape and unknown motion" (2014, 3 citations) propose novel methods that move beyond simplistic disc-shaped obstacles, enabling more realistic and robust predictions. By assuming obstacles are adversarial, her work in "Conservative Collision Prediction Among Polygons with Unknown Motion" (2013, 3 citations) provides a safety-critical framework for real-world applications. Lu’s research bridges theoretical geometry and practical robotics, offering tools that enhance the adaptability and safety of autonomous systems.