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Coded disc and laser radar fused odometer method and mapping method

A lidar and odometer technology, applied in computing, image analysis, image data processing, etc., can solve problems such as easy failure, and achieve the effect of low drift rate

Active Publication Date: 2022-02-08
TONGJI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

A closed-loop method based on iterative closest point (ICP) is proposed in the prior art, but it is easy to fail when the drift is too large

Method used

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  • Coded disc and laser radar fused odometer method and mapping method
  • Coded disc and laser radar fused odometer method and mapping method
  • Coded disc and laser radar fused odometer method and mapping method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0049] This embodiment provides an odometer method that integrates code discs and laser radars. Refer to figure 1 As shown, the method includes the following steps: collect the data of the wheel encoder and the steering wheel angle sensor, obtain the wheel odometer information based on the Ackermann steering geometry; obtain the point cloud data through the lidar, convert the format of the point cloud data, and obtain A laser scanning sequence; performing dedistortion and feature point extraction on the laser scanning sequence; performing pose optimization based on the extracted feature points to obtain a final high-frequency pose output.

Embodiment 2

[0051] Such as figure 1As shown, this embodiment provides an online mapping method, which is implemented based on a three-layer SLAM framework. In this framework, the first layer introduces the wheel odometry method based on Ackerman steering geometry, which outputs high-frequency motion in real time for point cloud de-distortion and serves as the initial value for pose optimization; the second layer uses An improved feature-based two-stage method based on the angle metric extracts edge features, planar features and degenerated features from point clouds, processes features at local scan scale and local map scale respectively to obtain more stable feature extraction results, and then The feature is analyzed, and the constraints on the sensor attitude are formed in the form of frame-local map, which is used for LiDAR odometry optimization; in the third layer, a graph-based method is applied to construct a model with LiDAR odometry factor, loop closure factor and optional GPS fa...

Embodiment 3

[0053] This embodiment provides a SLAM (simultaneous localization and mapping, synchronous localization and mapping) system WLAOM, which utilizes different sensors for real-time odometer and online map drawing; the improved feature-based LiDAR odometer method passes the wheel based on kinematics model The odometry method is enhanced to produce low-latency, low-drift attitude estimates, using a factor graph-based approach to fuse loop closure detection and GPS measurements, where self-aligning GPS factors are modeled to correct for attitude and estimate the relationship between GPS and local coordinate systems. transformation relationship between them. This allows the system to map vast areas covering many kilometers.

[0054] The system consists of five modules, receiving point cloud data directly from LiDAR and encoder data, and optional GPS measurement data via CAN, the system outputs optimized global trajectory and global point cloud map, both of which are compatible with G...

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Abstract

The invention relates to a coded disc and laser radar fused odometer method and a mapping method. The odometer method comprises the following steps: acquiring wheel odometer information through a wheel encoder and a steering wheel angle sensor; obtaining point cloud data through a laser radar, and performing format conversion on the point cloud data to obtain a laser scanning sequence; carrying out feature point extraction on the laser scanning sequence, wherein feature points comprise plane points and edge points; and taking the wheel odometer information as an initial optimization value, realizing pose optimization based on the feature points, obtaining a laser odometer result, taking the laser odometer result as a final odometer result, optimizing the pose based on a factor graph, a fused loop factor and an optional GPS (Global Positioning System) factor, and generating a global map on line through incremental smoothing and mapping algorithms. Compared with the prior art, the method has the advantages of low drift, low delay and the like.

Description

technical field [0001] The invention relates to the technical field of robot positioning, in particular to an odometer method and a mapping method that integrate code discs and laser radars. Background technique [0002] Simultaneous localization and mapping (SLAM) is a hot topic in the field of robotics. In recent years, the development of autonomous vehicles has brought new scenarios and challenges to SLAM. One of the most important challenges is self-localization, which is also the basic problem of SLAM, but it faces various challenges from the real world on a larger scale, such as lighting, weather, GPS signal quality, etc. Under this challenge, fusion methods using different types of sensors stand out, such as the combination of visual inertial method and lidar inertial method. [0003] The LiDAR Odometer and Mapping (LOAM) method uses two layers of optimization to achieve high-frequency LiDAR odometry and low-frequency LiDAR mapping and odometry correction, however, t...

Claims

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Application Information

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IPC IPC(8): G01C21/12G01S17/86G06T7/13G06T11/20
CPCG01C21/12G01S17/86G06T7/13G06T11/206Y02T10/40
Inventor 陈慧陈贤钦
Owner TONGJI UNIV
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