高速自律飛行のための堅牢なステレオ視覚慣性オドメトリ
Robust Stereo Visual Inertial Odometry for Fast Autonomous Flight
MSCKFを拡張したステレオ視覚慣性オドメトリS-MSCKFを提案し、単眼手法並みの計算コストで高い堅牢性を実現、17.5m/sの高速飛行で検証した。
著者: Ke Sun, Kartik Mohta, Bernd Pfrommer, Michael Watterson, Sikang Liu, Yash Mulgaonkar, Camillo J. Taylor, Vijay Kumar
分類: cs.RO
原文アブストラクト
In recent years, vision-aided inertial odometry for state estimation has matured significantly. However, we still encounter challenges in terms of improving the computational efficiency and robustness of the underlying algorithms for applications in autonomous flight with micro aerial vehicles in which it is difficult to use high quality sensors and pow- erful processors because of constraints on size and weight. In this paper, we present a filter-based stereo visual inertial odometry that uses the Multi-State Constraint Kalman Filter (MSCKF) [1]. Previous work on stereo visual inertial odometry has resulted in solutions that are computationally expensive. We demonstrate that our Stereo Multi-State Constraint Kalman Filter (S-MSCKF) is comparable to state-of-art monocular solutions in terms of computational cost, while providing signifi- cantly greater robustness. We evaluate our S-MSCKF algorithm and compare it with state-of-art methods including OKVIS, ROVIO, and VINS-MONO on both the EuRoC dataset, and our own experimental datasets demonstrating fast autonomous flight with maximum speed of 17.5m/s in indoor and outdoor environments. Our implementation of the S-MSCKF is available at https://github.com/KumarRobotics/msckf_vio.
