Ince, Omer Faruk Kim, Jun-Sik 2024-01-19T15:34:26Z 2024-01-19T15:34:26Z 2021-09-02 2021-01 1424-8220 https://pubs.kist.re.kr/handle/201004/117605 We present a novel simultaneous localization and mapping (SLAM) system that extends the state-of-the-art ORB-SLAM2 for multi-camera usage without precalibration. In this system, each camera is tracked independently on a shared map, and the extrinsic parameters of each camera in the fixed multi-camera system are estimated online up to a scalar ambiguity (for RGB cameras). Thus, the laborious precalibration of extrinsic parameters between cameras becomes needless. By optimizing the map, the keyframe poses, and the relative poses of the multi-camera system simultaneously, observations from the multiple cameras are utilized robustly, and the accuracy of the shared map is improved. The system is not only compatible with RGB sensors but also works on RGB-D cameras. For RGB cameras, the performance of the system tested on the well-known EuRoC/ASL and KITTI datasets that are in the stereo configuration for indoor and outdoor environments, respectively, as well as our dataset that consists of three cameras with small overlapping regions. For the RGB-D tests, we created a dataset that consists of two cameras for an indoor environment. The experimental results showed that the proposed method successfully provides an accurate multi-camera SLAM system without precalibration of the multi-cameras. English MDPI TIMA SLAM: Tracking Independently and Mapping Altogether for an Uncalibrated Multi-Camera System Article 10.3390/s21020409 1 SENSORS, v.21, no.2, pp.1 - 16 SENSORS 21 2 1 16 scie scopus 000611716800001 2-s2.0-85099016677 Chemistry, Analytical Engineering, Electrical & Electronic Instruments & Instrumentation Chemistry Engineering Instruments & Instrumentation Article SLAM multi-camera self extrinsic camera calibration multi-edge based optimization