SLAM (Simultaneous Localization and Mapping) back-end optimization-oriented Schur elimination accelerator

An accelerator and data cache technology, applied in the field of SLAM system hardware accelerator design, to achieve the effect of reducing data correlation, reducing the number of visits, and improving computing performance

Active Publication Date: 2021-07-27
ZHEJIANG UNIV
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Problems solved by technology

[0005] In order to overcome the shortcomings that BA cannot be realized on mobile platforms with limited performance and power consumption in the prior art, the present invention provides...

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  • SLAM (Simultaneous Localization and Mapping) back-end optimization-oriented Schur elimination accelerator
  • SLAM (Simultaneous Localization and Mapping) back-end optimization-oriented Schur elimination accelerator
  • SLAM (Simultaneous Localization and Mapping) back-end optimization-oriented Schur elimination accelerator

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Embodiment Construction

[0026] The present invention will be described in detail below in conjunction with the accompanying drawings and algorithm principles.

[0027] The mainstream of the SLAM backend uses the LM algorithm to optimize the coordinates of the camera pose and landmark points. The algorithm has sparsity characteristics in SLAM, and the Schur elimination algorithm can be used to reduce the amount of computation; the algorithm can be divided into four parts: Jacobian matrix update, Schur elimination, equation solving and incremental evaluation, in which the Schur elimination process consumes With a large number of computing resources, the process can be divided into four stages: H matrix calculation, matrix inversion, Schur complement update and Schur complement fusion.

[0028] The H matrix calculation stage is used to solve the sub-matrix C of the H matrix according to the reprojection loss function about the Jacobian matrix of the camera pose and the landmark point, the difference blo...

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Abstract

A SLAM rear-end optimization-oriented Schur elimination accelerator comprises an algorithm control module used for completing maintenance of a control signal; a prefetching control module used for completing prefetching operation of input projection error data and Jacobian matrix data; a data cache access control module used for completing address generation and read-write requests of data cache, including address maintenance of different matrix data and advanced initiation of read requests; an operation module used for completing matrix multiplication, matrix inversion, matrix addition and subtraction and matrix and constant multiplication; a data rearrangement and control unit used for completing data recombination; an input and output caching unit used for completing advanced caching of prefetch input and data caching during output; and a data caching unit used for completing caching of intermediate data in the operation process. According to the accelerator, hardware acceleration is carried out on the Schur elimination process by proposing an FPGA accelerator scheme, so that a traditional embedded platform can execute the BA optimization process with higher performance.

Description

technical field [0001] The invention relates to the field of SLAM system hardware accelerator design, in particular to a Shure elimination accelerator oriented to SLAM back-end optimization. Background technique [0002] Bundle Adjustment (BA) is an algorithm that jointly optimizes camera parameters and 3D feature point positions. BA is a computationally intensive algorithm in Simultaneous Localization And Mapping (SLAM), which has a wide range of applications. In the field of SLAM, BA applies its back-end optimization link, which can significantly reduce the impact of sensor noise on the SLAM system. Therefore, BA enables the mobile robot to more accurately model its own position and environmental characteristics, so as to better perform mobile tasks. [0003] In the early SLAM research, the development of the back-end algorithm of the SLAM system focused on the exploration based on the filtering algorithm, and the extended Kalman filtering algorithm occupied a dominant p...

Claims

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Application Information

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IPC IPC(8): G06T1/20G06T1/60
CPCG06T1/20G06T1/60
Inventor 冯彪李世云赵昀昊
Owner ZHEJIANG UNIV
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