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

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...

AI Technical Summary

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 a Shure elimination accelerator oriented to SLAM back-end optimization, which can better meet the requirements of embedded platforms for algorithm computing performance and power requirements

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