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全向重载自动引导车（Automated Guided Vehicle,AGV）在不同工况下的舵轮形变会造成车轮里程计测量误差，进而降低导航定位精度。建立全向重载AGV的垂向动力学模型与车轮弹性变形模型以定量分析车轮变形，再利用运动学模型将车轮变形对定位误差的影响映射为AGV定位误差模型，基于此模型提出了一种融合车轮里程计和激光雷达信息的方法，其引入平方根扩展卡尔曼滤波器（Square Root Extended Kalman Filter,SREKF），融合激光雷达和轮式里程计的位姿数据，并添加误差补偿项以修正预测模型，从而修正舵轮变形导致的车轮里程计误差。经过仿真验证了重载条件下舵轮产生的变形误差，且实验结果表明采用所提补偿算法能将定位精度提升54.5%。所提算法能提升AGV在一般工况下的定位精度。
Abstract：The deformation of steering wheel in the heavy load condition of omnidirectional Automated Guided Vehicles(AGVs)can cause measurement errors in wheel odometers,which in turn reduces navigation accuracy. A vertical dynamic model and a wheel elasticity deformation model were established for the omnidirectional heavy load AGV,and their effects were mapped to a positioning error model using a kinematic model. Based on this model,a method that integrates wheel odometer and LiDAR information was proposed,which introduces a Square Root Extended Kalman Filter(SREKF)to fuse the pose data from LiDAR and wheel odometer and adds an error compensation term to correct the prediction model,thus correcting the wheel odometer errors caused by heavy load conditions. The simulation verifies the deformation error caused by the steering wheel under heavy load conditions,and experimental results show that the proposed compensation algorithm can improve the positioning accuracy by54.5%. The proposed algorithm can improve the positioning accuracy of AGVs under heavy load conditions.
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基本信息:
中图分类号:TP23
引用信息:
[1]耿郑一,汪步云.全向重载AGV融合定位误差补偿算法研究[J].淮阴工学院学报,2025,34(02):11-18.
基金信息:
安徽省重点研究与开发计划“基于生机多模态信息共融的助力行走型下肢外骨骼机器人产品研发”（202004a05020013）
2023-11-07
2023
2024-04-01
2024-03-28
2024
1
2025-04-15
2025-04-15