高速ダイレクトステレオビジュアルSLAM
Fast Direct Stereo Visual SLAM
特徴点検出・マッチングを使わず、DSOをステレオに拡張して光度誤差最小化でスケールを最適化し、LiDAR風スキャンと記述子でループ閉じ込みを行う高速で堅牢なステレオビジュアルSLAMを提案した論文。
著者: Jiawei Mo, Md Jahidul Islam, Junaed Sattar
分類: cs.RO
原文アブストラクト
We propose a novel approach for fast and accurate stereo visual Simultaneous Localization and Mapping (SLAM) independent of feature detection and matching. We extend monocular Direct Sparse Odometry (DSO) to a stereo system by optimizing the scale of the 3D points to minimize photometric error for the stereo configuration, which yields a computationally efficient and robust method compared to conventional stereo matching. We further extend it to a full SLAM system with loop closure to reduce accumulated errors. With the assumption of forward camera motion, we imitate a LiDAR scan using the 3D points obtained from the visual odometry and adapt a LiDAR descriptor for place recognition to facilitate more efficient detection of loop closures. Afterward, we estimate the relative pose using direct alignment by minimizing the photometric error for potential loop closures. Optionally, further improvement over direct alignment is achieved by using the Iterative Closest Point (ICP) algorithm. Lastly, we optimize a pose graph to improve SLAM accuracy globally. By avoiding feature detection or matching in our SLAM system, we ensure high computational efficiency and robustness. Thorough experimental validations on public datasets demonstrate its effectiveness compared to the state-of-the-art approaches.
