Lindsey Andrews

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About

Lindsey Andrews is a researcher in robotics and control systems, with a primary focus on optimal path-following and adaptive dynamic programming for mobile robots. Her most-cited work, "Online approximate optimal path-following for a mobile robot" (2014), introduces a novel approach to solving infinite horizon optimal control problems for unicycle-type robots. By employing adaptive dynamic programming techniques, Andrews developed a method that uses adaptive update laws to estimate unknown value functions in real time, enabling robots to approximate optimal path-following strategies without requiring full system knowledge. This work, with 9 citations, has contributed to advancing autonomous navigation capabilities, particularly in scenarios where computational efficiency and adaptability are critical. Andrews's research bridges theoretical optimal control with practical robotic applications, offering solutions that improve the performance of mobile robots in dynamic environments. Her contributions are valuable for researchers and engineers working on autonomous systems, path planning, and real-time control, demonstrating how adaptive methods can enhance robotic autonomy and reliability.