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ICAR 2021 RPV SLAM (3DMMAI) Paper Accepted

Dr. Jungwon Kang, Dr Yujia Zhang and Zhen Liu (2nd Year PhD Student) in the lab published their paper on RPV-SLAM: Range-augmented Panoramic Visual SLAM for Mobile Mapping System with Panoramic Camera and Tilted LiDAR in the the 20th International Conference on Advanced Robotics  (ICAR 2021). He will present his research work at the conference virtually during the conference period starting from Dec. 07 ~ Dec. 10, 2021. The title of Dr Kang’s paper is “RPV-SLAM: Range-augmented Panoramic Visual SLAM for Mobile Mapping System with Panoramic Camera and Tilted LiDAR”.


RPV-SLAM: Range-augmented Panoramic Visual SLAM for Mobile Mapping System with Panoramic Camera and Tilted LiDAR

Abstract: A LiDAR-assisted panoramic visual simultaneous localization and mapping (SLAM) system for a mobile mapping system (MMS) is presented in this paper. The feasibility research on the SLAM for MMS with a panoramic camera and a tilted LiDAR without GPS/IMU sparked our interest. Because of the significant disparity in spatial sensing coverage, we show that employing a panoramic camera as a primary
sensor for SLAM is more suitable than using a tilted LiDAR in this particular sensor combination. Existing panoramic visual SLAM systems, on the other hand, produce up-to-scale results, making them inappropriate for many applications that require metrically-scaled results. We develop a panoramic visual SLAM system that uses LiDAR points to generate metrically-scaled outputs to address this constraint. First, the suggested SLAM system augments visual features with ranges generated from LiDAR points. Following that, the visual features are fed into the SLAM pipeline, which performs tracking, local mapping, and loop closing. Finally, the scale information in the ranges augmented to visual features is integrated into the SLAM pipeline via the production of metrically-scaled map points, eventually leading to metrically-scaled SLAM results. Extensive testing in challenging outdoor conditions has proven the effectiveness and robustness of the proposed SLAM system.

A recorded oral presentation of the ICAR 2021 conference paper (Prepared by Dr Jungwon Kang and Dr Yujia).

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