基于双目视觉的运动目标检测与三维重建

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中文摘要：移动机器人凭借其工作性能可靠、减少生产制造成本等优势,在现代集成智能制造业中具有广阔的市场应用前景.但目前移动机器人室内环境感知系统存在感知维度单一、精度不高等问题,往往难以满足多维度实时精确感知环境的需求.因此,在模拟物流储仓的实验室环境下构建了一种可同时进行二维动态目标检测和三维场景地图重建的环境感知系统,将双目相机采集的图像分别输入增加树形特征融合模块的改进YOLOv3网络与加入带色彩恢复的多尺度视网膜增强算法和关键帧筛选机制的优化RTAB-MAP算法,运行结果在机器人可视化平台实时显示,从而进行多维度环境感知,满足多任务需求.实验结果表明,动态目标检测中查准率与查全率较原算法分别提高1.78％和1.73％,检测耗时为16.57ms/f,平均定位误差为1.49％;改进后的RTAB-MAP算法相较原算法各误差均显著下降,实际室内场景重建中三维点云地图质量更佳.

外文标题：Moving target detection and 3D reconstruction based on binocular vision

外文摘要：Mobile robots have broad market application prospects in modern integrated intelligent manufacturing due to their advantages such as reliable performance and reduced manufacturing costs.However,there exist problems such as single perception dimension,low precision in the indoor environment perception system of mobile robots,which is hard to meet the demands of multi-dimensional real-time and accurate perception of the environment at pres-ent.Therefore,an environment perception system that could simultaneously perform 2D dynamic target detection and 3D scene map reconstruction in a laboratory environment was constructed by simulating a logistics warehouse,the images collected by the binocular camera were respectively input into the improved You Only Look Once version 3(YOLOv3)network fused with Tree-structured Feature Aggregation(TFA)module and the optimized RTAB-MAP algorithm with Multi-Scale Retinex with Color Restoration(MSRCR)algorithm and key frame filtering mech-anism,thus the results were displayed in Robot Visualization tool(RVIZ)in real time and achieved multi-dimen-sional environment perception,so that it could meet the needs of multi-tasking.The experimental results showed that the precision and recall in dynamic target detection were improved by 1.78％and 1.73％respectively compared with the original algorithm,the detection time was 16.57ms/f,and the average positioning error was 1.49％.Com-pared with the original algorithm,the errors of the improved RTAB-MAP algorithm were significantly reduced,and the quality of the 3D point cloud map in the actual indoor scene reconstruction was better.

外文关键词：

binocular visionmoving target detection3D reconstructionYOLOv3mobile robot

作者：

赵珊珊、米曾真、陈韧

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作者单位：

重庆理工大学机械工程学院,重庆 400054

关键词：

双目视觉运动目标检测三维重建 YOLOv3 移动机器人

基金：

国家自然科学基金资助项目重庆市教委科学技术研究资助项目重庆市教委科学技术研究资助项目重庆市自然科学基金资助项目重庆市研究生科研创新资助项目

项目编号：

61901068KJQN201901150KJQN202001131cstc2021jcyjmsxmX0525CYS21467

出版年：

2024

DOI：

10.13196/j.cims.2022.0338

计算机集成制造系统

中国兵器工业集团第210研究所

计算机集成制造系统

CSTPCD北大核心

影响因子：1.092

ISSN：1006-5911

年,卷(期)：2024.30(7)