信息与控制2025，Vol.54Issue(6)：851-865,15.DOI:10.13976/j.cnki.xk.2024.4202
越野环境下基于多维度评分模型的多传感器自适应融合定位算法
Multi-sensor Adaptive Fusion Positioning Algorithm Based on Multi-dimensional Scoring Model for Off-road Environment
摘要
Abstract
The complex terrain,vibrations,and other factors in off-road environments can cause sensor degradation and significantly affect the performance of visual-inertial odometry(VIO).To address this issue,we propose an adaptive fusion algorithm combining the global navigation satellite system(GNSS)and VIO based on a multidimensional scoring model.First,during the initialization,we construct an extended state variable window to estimate the coordinate transformation and apply the interpolation algorithm to reducing the impact of time synchronization errors.Second,we develop a scoring model incorporating the motion,rotation,and consistency dimensions to assess the reliability of the sensor data in real time.Based on the scoring results,we adaptively adjust the noise covari-ance matrix of the sensors to optimize the data fusion effect and mitigate the effect of sensor degra-dation.Finally,we conduct experiments in an agricultural scenario and three different campus sce-narios.The results reveal that the proposed algorithm effectively addresses sensor degradation and significantly improves the positioning accuracy of the VIO system(with an average improvement of 79％).Compared with GSI-SLAM,a tightly coupled GNSS-VIO algorithm designed for arable farming,the proposed algorithm improves the positioning accuracy by 37％.关键词
越野环境/传感器退化/多维度评分模型/GNSS-VIO自适应融合Key words
off-road environment/sensor degradation/multi-dimensional scoring model/adaptive GNSS-VIO fusion分类
信息技术与安全科学引用本文复制引用
魏鸿扬,魏国亮,蔡洁,纪周..越野环境下基于多维度评分模型的多传感器自适应融合定位算法[J].信息与控制,2025,54(6):851-865,15.基金项目
国家自然科学基金项目(62273239) （62273239）
上海市"科技创新行动计划"国内科技合作项目(20015801100) （20015801100）
