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• W2796298276 abstract "This paper presents a non-iterative solution to RGB-D-inertial odometry system. Traditional odometry methods resort to iterative algorithms which are usually computationally expensive or require well-designed initialization. To overcome this problem, this paper proposes to combine a non-iterative front-end (odometry) with an iterative back-end (loop closure) for the RGB-D-inertial SLAM system. The main contribution lies in the novel non-iterative front-end, which leverages on inertial fusion and kernel cross-correlators (KCC) to match point clouds in frequency domain. Dominated by the fast Fourier transform (FFT), our method is only of complexity $mathcal{O}(nlog{n})$, where $n$ is the number of points. Map fusion is conducted by element-wise operations, so that both time and space complexity are further reduced. Extensive experiments show that, due to the lightweight of the proposed front-end, the framework is able to run at a much faster speed yet still with comparable accuracy with the state-of-the-arts." @default.
• W2796298276 created "2018-04-13" @default.
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• W2796298276 date "2017-10-16" @default.
• W2796298276 modified "2023-09-28" @default.
• W2796298276 title "Non-iterative RGB-D-inertial Odometry" @default.
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• W2796298276 hasPublicationYear "2017" @default.
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