Andrew Holliday

Papers

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About

Andrew Holliday is a researcher advancing the frontiers of robotic perception and autonomous navigation, with a focus on visual localization and active perception. His work addresses critical challenges in enabling robots to operate reliably in complex, real-world environments. Holliday’s most influential contribution is his 2018 paper, "Scale-Robust Localization Using General Object Landmarks," which tackles the problem of visual localization under extreme scale changes—such as when a drone localizes in a map built from high-altitude imagery. While existing methods falter beyond a 3× scale difference, his approach demonstrates robust performance, a key capability for long-distance loop closure and multi-altitude mapping. This work has garnered 12 citations, reflecting its relevance to the field. In a second notable paper (3 citations), Holliday explores active gaze control to enhance visual odometry and SLAM during navigation, improving odometric estimate quality by focusing on feature stability. Together, these contributions highlight his innovative blend of landmark-based and active perception strategies, positioning him as a promising voice in robotics research with practical implications for autonomous systems.