计算机工程与应用2024，Vol.60Issue(19)：120-129,10.DOI:10.3778/j.issn.1002-8331.2308-0119
CPU环境下多传感器数据融合的机器人3D目标检测方法
Multi-Sensor Data Fusion for Robotic 3D Target Detection in CPU Environment
摘要
Abstract
Real-time and accurate 3D object detection algorithms can provide target position and shape information,en-suring efficient navigation and effective obstacle avoidance for mobile robots,among other tasks.Existing 3D object de-tection algorithms heavily rely on the computational capabilities of hardware devices.A multi-sensor fusion 3D object de-tection method that can be deployed in mobile robot CPU environments has been proposed to reduce hardware require-ments while ensuring detection accuracy.The method combines 2D object detection and point cloud clustering tech-niques.It utilizes 2D object detection technology to obtain object detection information from images,then performs point cloud segmentation within the detection bounding boxes based on the spatial mapping relationship between cameras and lidars.The segmented point clouds are further clustered and processed for information extraction,achieving 3D object de-tection and localization capabilities.By comparing with the classical multi-sensor 3D target detection algorithm MVX-Net,the algorithm in this paper has better detection accuracy with smaller computational complexity.Furthermore,the method is deployed and analyzed on actual mobile robot CPU devices at the edge terminal,achieving a processing speed of 0.069 seconds per frame,satisfying the 10 Hz laser radar frequency requirement.关键词
3D目标检测/多传感器数据融合/CPU/移动机器人Key words
3D object detection/multi-sensor data fusion/CPU/mobile robot分类
信息技术与安全科学引用本文复制引用
楼进,刘恩博,唐炜,张仁远..CPU环境下多传感器数据融合的机器人3D目标检测方法[J].计算机工程与应用,2024,60(19):120-129,10.基金项目
陕西省自然科学基础研究计划面上项目(2021JM-072) （2021JM-072）
中国高校产学研创新基金(2021ZYA02014) （2021ZYA02014）
西北工业大学硕士研究生实践创新能力培育基金(PF2023106). （PF2023106）
