基于无人机应用的协同vSLAM

Xiaodong Li, N. Aouf
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引用次数: 0

摘要

本文研究了协同视觉SLAM在无人机中的应用。该研究利用综合方法研究了配备立体视觉相机系统的多架无人机的协同数据融合策略,其中协同估计通过信息过滤和协方差交叉技术实现,以研究与单独使用vSLAM的单架无人机相比,在噪声鲁棒性和位置确定和制图过程的准确性方面的潜在改进。通过比较协同无人机增强滤波方案与未进行融合增强的单个无人机实现方案的误差和鲁棒性,进一步讨论了所实现的性能增强。最后,还讨论了本研究提出的方法的相对优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cooperative vSLAM based on UAV application
This paper addresses research into the application of cooperative visual SLAM for utilization within UAVs. The research utilized a synthetic approach to examine a cooperative data fusing strategy for multiple UAVs equipped with stereo vision camera systems, where the collaborative estimation was implemented with an information filter and covariance intersection technique to investigate potential improvements in robustness to noise and accuracy of location determination and mapping processes, when compared to a single UAV employing vSLAM alone. The achieved performance enhancement is further discussed in terms of the demonstrated error and robustness as a comparison between the cooperative UAV enhanced filtering scheme versus the single UAV implementation without the proposed fusing enhancements. To conclude, the relative merits of the methodology proposed by this research are also discussed.
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