Stereo DSO: Large-Scale Direct Sparse Visual Odometry with Stereo Cameras
Rui Wang,Martin Schworer,Daniel Cremers +2 more
- pp 3923-3931
TLDR
Stereo Direct Sparse Odometry (Stereo DSO) as discussed by the authors integrates constraints from static stereo into the bundle adjustment pipeline of temporal multi-view stereo to improve tracking accuracy and robustness.Abstract:
We propose Stereo Direct Sparse Odometry (Stereo DSO) as a novel method for highly accurate real-time visual odometry estimation of large-scale environments from stereo cameras. It jointly optimizes for all the model parameters within the active window, including the intrinsic/extrinsic camera parameters of all keyframes and the depth values of all selected pixels. In particular, we propose a novel approach to integrate constraints from static stereo into the bundle adjustment pipeline of temporal multi-view stereo. Real-time optimization is realized by sampling pixels uniformly from image regions with sufficient intensity gradient. Fixed-baseline stereo resolves scale drift. It also reduces the sensitivities to large optical flow and to rolling shutter effect which are known shortcomings of direct image alignment methods. Quantitative evaluation demonstrates that the proposed Stereo DSO outperforms existing state-of-the-art visual odometry methods both in terms of tracking accuracy and robustness. Moreover, our method delivers a more precise metric 3D reconstruction than previous dense/semi-dense direct approaches while providing a higher reconstruction density than feature-based methods.read more
Citations
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Journal ArticleDOI
Monocular Visual-Inertial Odometry for Agricultural Environments
TL;DR: The accuracy of autonomous robot localization using a monocular visual-inertial odometry system (VIO) is significantly reduced in an agricultural environment compared to an urban and indoor environment due to the unstructured scenes with unstable features, variation of light conditions, and rugged terrain, and the absolute trajectory error can be at least reduced by 69% compared with the VINS-mono.
Journal ArticleDOI
Accuracy improvement of cooperative localization using UAV and UGV
Ryoga Shimizu,Yasunori Sugita +1 more
TL;DR: In this article , the UAV point estimation result is converted to a normal distribution by giving a fixed covariance matrix in order to introduce it as the observation likelihood of the UGV.
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Complete Closed-Form and Accurate Solution to Pose Estimation From 3D Correspondences
TL;DR: In this paper , a complete and accurate closed-form solution for a weighted least-squares problem is proposed, which is able to solve the problem in any non-degenerate case and it is accurate since it is guaranteed to find the global optimal estimate of the weighted least squares problem.
Journal ArticleDOI
Overview of Multi-Robot Collaborative SLAM from the Perspective of Data Fusion
Weifeng Chen,Xiyang Wang,Shanping Gao,Guang Peng Shang,Chengjun Zhou,Zhenxiong Li,Chonghui Xu,Kai Hu +7 more
TL;DR: Multi-robot collaborative SLAM (VSLAM) as discussed by the authors is a current research hotspot, and relevant algorithms are being updated rapidly, which can resolve individual cost, global error accumulation, computational load, and risk concentration problems faced by single robot SLAM schemes.
Book ChapterDOI
Novel Approaches for Periodic Depth Enhancement in Visual SLAM
TL;DR: In this paper , the authors proposed to enhance each keyframe or each camera frame periodically with depth information to improve the scale drift in visual SLAM systems, which achieved comparable or more accurate results than stereo trajectories.
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