An orb-slam hardware accelerator

Abstract

The invention discloses an ORB-SLAM hardware accelerator, which comprises: an FPGA hardware acceleration module and which is used for accelerating feature extraction and feature matching; a sensor module which is used for capturing images; And a processor system which is used as a host for controlling the FPGA hardware acceleration module and the sensor module, and is responsible for operating pose estimation, pose optimization and map updating. The invention utilizes the FPGA hardware acceleration module to accelerate the process with the largest calculation and the most time consuming in theORB-SLAM process, can effectively improve the running speed of the ORB-SLAM and reduce the power consumption, greatly improve the energy consumption ratio, and reduce the difficulty of ORB-SLAM deployment on power-constrained platforms.

Description

technical field

[0001] The invention relates to the field of autonomous navigation, in particular to an ORB-SLAM hardware accelerator. Background technique

[0002] SLAM (simultaneous positioning and mapping) is one of the most critical technologies in the field of autonomous navigation. It enables the autonomous navigation system to build incremental maps of the surrounding environment based on information captured by sensors in an unknown environment. At the same time determine their own position in the environment. SLAM is widely used in the fields of self-driving cars, autonomous navigation robots, virtual reality and augmented reality, and is a crucial technology.

[0003] ORB-SLAM is a visual SLAM based on feature point method of ORB descriptor. It is a very efficient and robust SLAM system that has received extensive research attention. Existing ORB-SLAM systems can only run on traditional computing platforms (CPU, GPU), which leads to their relatively low performa...

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