Papers
2
Total Citations
13
H-Index
2
About
Linya Fu is a roboticist advancing the frontier of autonomous perception and sensor intelligence. Her research centers on two critical pillars of modern robotics: acoustic scene understanding and multi-sensor calibration. In her highly cited work, "I-ASM: Iterative Acoustic Scene Mapping for Enhanced Robot Auditory Perception in Complex Indoor Environments" (2024, 8 citations), Fu tackles the formidable challenge of mapping multiple sound sources in cluttered spaces. She introduces a novel particle filter-based iterative framework that operates without relying on prior data association or SLAM—a breakthrough that enables robots to "hear" and localize their environment with unprecedented accuracy. Complementing this, her 2025 paper on "Observability-Aware Active Calibration of Multisensor Extrinsics for Ground Robots" (5 citations) revolutionizes sensor alignment. By leveraging online trajectory optimization, Fu eliminates the need for complex, human-operated calibration processes, allowing ground robots to autonomously and optimally calibrate their sensor suites during operation. Her work directly enhances robot autonomy in real-world settings, from search-and-rescue to industrial inspection. With citation counts already reflecting the immediate relevance of her contributions, Fu is establishing herself as a rising leader in perceptually-aware robotics, bridging the gap between theoretical sensor fusion and practical, deployable systems.
Research Focus
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Top Papers
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