Sean Katagiri

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About

Sean Katagiri is a robotics researcher whose work lies at the intersection of autonomous navigation, perception, and state estimation. His primary research focuses on developing algorithms that enable robots to move intelligently through complex environments by actively considering their own perceptual limitations. In his most-cited work, "Adaptive Heading for Perception-Aware Trajectory Following" (2023, 5 citations), Katagiri introduced a novel approach that allows a robot to dynamically adjust its heading during motion. Instead of blindly following a path, the robot adapts its orientation to improve feature tracking in its mapped surroundings, thereby enhancing localization accuracy. This contribution is particularly valuable for long-duration autonomous missions where maintaining reliable state estimation is critical. By bridging the gap between path planning and perception, Katagiri’s work helps robots make smarter, more robust decisions in real-world settings. His research is especially relevant for applications in field robotics, where environmental conditions can degrade sensor performance. Through his focus on perception-aware control, Katagiri is helping to build the next generation of autonomous systems that are not only mobile, but also perceptually aware.