Yiren Lu

ShanghaiTech University, Shanghai Institute of Microsystem and Information Technology, Jiangsu Normal University

Papers

Total Citations

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About

Yiren Lu is a researcher at the forefront of robotics perception and human-robot interaction, with key contributions in sensor calibration, object detection, and wearable haptic interfaces. Their most impactful work, "Multical" (2022, 11 citations), introduces a general spatiotemporal calibration method for multiple IMUs, cameras, and LiDARs—even those without overlapping fields of view—addressing a critical challenge in autonomous driving and robotics. This work enables more accurate multi-sensor fusion for robust perception systems. Lu also advanced practical object detection for mobile robots in "Improving CNN-based Planar Object Detection with Geometric Prior Knowledge" (2020, 9 citations), which integrates geometric priors to overcome limitations of standard CNN detectors in real-world deployment. More recently, Lu has explored the emerging field of wearable haptic interfaces (2023, 3 citations), contributing to the development of new control terminals for human-robot communication and virtual reality. Through these diverse contributions—spanning calibration, perception, and interaction—Lu demonstrates a commitment to bridging theoretical advances with practical robotic systems, making their work valuable for both researchers and engineers building next-generation autonomous and interactive robots.