K. Graves

United States Naval Research Laboratory, United States Naval Academy

Papers

Total Citations

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About

K. Graves is a pioneer in autonomous mobile robotics, with a career focused on solving the fundamental “chicken-and-egg” problem of simultaneous localization and mapping (SLAM). His research centers on creating robust, adaptive systems that can operate in rapidly changing environments, emphasizing the integration of perception, planning, and control as a core research challenge. Graves’s most influential work, “Integrating map learning, localization and planning in a mobile robot” (2002, 17 citations), champions a unified representation scheme—specifically, evidence grids—to allow different robotic processes to work seamlessly together. He further advanced the field with “Continuous localization in changing environments” (2002, 9 citations), a technique that enables robots to maintain accurate position estimates through regular, small odometry corrections without relying on static landmarks. His earlier work on the ARIEL platform (1997, 6 citations) directly tackled the exploration dilemma: a robot needs a map to localize, but a location to build a map. By demonstrating that a common representation could serve both mapping and localization, Graves laid essential groundwork for modern autonomous navigation, influencing how robots explore unknown spaces today.