Author:
ZHANG Chi,YANG Zhong,XU Hao,LIAO Luwei,ZHU Tang,LI Guotao,YANG Xin,ZHANG Qiuyan
Abstract
Self-localization and orientation estimation are the essential capabilities for mobile robot navigation. In this article, a robust and real-time visual-inertial-GNSS(Global Navigation Satellite System) tightly coupled pose estimation (RRVPE) method for aerial robot navigation is presented. The aerial robot carries a front-facing stereo camera for self-localization and an RGB-D camera to generate 3D voxel map. Ulteriorly, a GNSS receiver is used to continuously provide pseudorange, Doppler frequency shift and universal time coordinated (UTC) pulse signals to the pose estimator. The proposed system leverages the Kanade Lucas algorithm to track Shi-Tomasi features in each video frame, and the local factor graph solution process is bounded in a circumscribed container, which can immensely abandon the computational complexity in nonlinear optimization procedure. The proposed robot pose estimator can achieve camera-rate (30 Hz) performance on the aerial robot companion computer. We thoroughly experimented the RRVPE system in both simulated and practical circumstances, and the results demonstrate dramatic advantages over the state-of-the-art robot pose estimators.
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献