Loop detection method and system, readable storage medium and electronic equipment

Abstract

The invention provides a loopback detection method and system, a readable storage medium and electronic equipment, and the method comprises the steps: receiving node data, carrying out the Hash codingbased on a GPS position in the node data to obtain a key value, and achieving the nearly real-time loopback retrieval efficiency while enabling the global position (GPS) information received by a vehicle to be utilized separately; searching a historical node set which has the same key value and comprises at least one historical node from a historical GPS position code library, screening a targetloop node from the historical node set, constructing a loop based on the target node and the target loop node, and rapidly eliminating a pseudo loop formed by long-time parking by adopting the constraint of time and track length, thereby improving the precision of track optimization.

Description

technical field [0001] The invention relates to the technical field of automatic driving, in particular to a loop detection method. Background technique [0002] High-precision maps can provide accurate three-dimensional environmental information, which is an indispensable element for realizing L4 unmanned driving. Using lidar as the main sensor and using Simultaneous Localization and Mapping (SLAM) technology to automatically construct high-precision maps is the current mainstream trend. [0003] A complete SLAM system can be divided into two parts, front-end and back-end. Among them, the front-end odometer estimates the position and attitude (pose) of the unmanned vehicle in real time through frame-to-frame matching; Over time, errors gradually accumulate, which will cause trajectory drift or even divergence. The backend mainly optimizes the entire trajectory through loop detection to ensure the accuracy of the trajectory. The so-called loopback detection means that the ...

AI Technical Summary

Problems solved by technology

When the unmanned vehicle is moving in a small area, the bag-of-words model can be used for loop detection to achieve high accuracy. , leading to a gradual decline in retrieval accuracy

In addition, using the bag-of-words model for loopback retrieval requires additional feature extraction operations. For SLAM systems, this will undoubtedly increase the computational cost of the entire SLAM system and affect the operating efficiency of the SLAM system.

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