Multi-feature fusion IGV positioning and mapping method based on 3D laser radar

Abstract

The invention discloses a multi-feature fusion IGV positioning and mapping method based on a 3D laser radar. The method mainly comprises four processes of data acquisition processing, scanning matching and local map construction, back-end optimization and loopback detection. Data acquisition processing is data processing of the 3D laser radar sensor; according to the scanning matching and local map construction, a frame-subgraph matching mode is adopted for processed laser point cloud data, a three-dimensional landmark with multi-feature information such as angle, distance and reflection intensity is used for resolving an initial pose, and a local optimal subgraph is constructed by occupying a grid map; according to back-end optimization, for continuously iterated sub-graphs, a graph optimization strategy is adopted, an optimization problem is solved by using a Gaussian Newton method, and a solving process is accelerated by using a three-dimensional landmark, so that accumulated errors are eliminated; all tracks are stored in loopback detection, a multi-resolution map is adopted, calculation is accelerated through a branch and bound method, and closed-loop detection is completed. Finally, high-precision positioning and mapping of the AGV are realized.

Description

technical field [0001] The invention belongs to the field of automatic control, and in particular relates to a multi-feature fusion IGV positioning and mapping method based on 3D laser radar. Background technique [0002] With the development of warehousing and logistics, our country has shifted from a labor-based low-end manufacturing industry to an artificial intelligence technology industry. Factors such as insufficient labor supply have prompted the continuous development of the mobile robot industry. In the future, China will become a big country in the manufacturing and application of mobile robots. .At present, most of the IGVs widely used in rush logistics use 2D laser slam as the positioning and mapping method. When the environment is symmetrical, it is difficult to achieve high-precision positioning and mapping, and only obtain flat map information. For navigation, avoidance Additional sensors need to be added to prevent obstacles, which not only increases economic...

AI Technical Summary

Problems solved by technology

[0002] With the development of warehousing and logistics, our country has shifted from a labor-based low-end manufacturing industry to an artificial intelligence technology industry. Factors such as insufficient labor supply have prompted the continuous development of the mobile robot industry. In the future, China will become a big country in the manufacturing and application of mobile robots. .At present, most of the IGVs widely used in rush logistics use 2D laser slam as the positioning and mapping method. When the environment is symmetrical, it is difficult to achieve high-precision positioning and mapping, and only obtain flat map information. For navigation, avoidance Additional sensors need to be added to prevent obstacles, which not only increases economic costs, but also poses certain safety hazards

Images