Multi-level on-board data fusion for 2D safety enhanced by 3D perception for AGVs

2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2015-11-02 DOI:10.1109/ICCP.2015.7312636

C. Stimming, Annette Krengel, Markus Boehning, A. Vatavu, Szilard Mandici, S. Nedevschi

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引用次数: 2

Abstract

Modern AGVs are equipped with several safety laser scanners with a combined 360 deg field of view around the AGV to detect and subsequently avoid collisions with other AGVs, structural elements and, most importantly, workers. This contactless environment perception approach fulfils current safety legislation and safety regulations for driverless industrial trucks. However, obstacle detection is limited to a 2D plane parallel and close to the ground, unable to detect protruding or hanging objects in the path of the AGV. In order to avoid collisions with these kinds of objects as well, the idea of PAN-Robots is to enhance the existing 2D safety by a 3D perception system based on an omnidirectional stereo camera. This paper describes the multi-level on-board sensor data fusion strategies implemented in the PAN-Robots project. The fused information of tracked and classified objects is not only used for on-board risk assessment and emergency collision avoidance, but is also communicated to the global control center for advanced fleet coordination and intelligent AGV navigation.

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多层次车载数据融合，通过 AGV 的 3D 感知增强 2D 安全性

现代 AGV 配备了多个安全激光扫描仪，可在 AGV 周围 360 度范围内探测并避免与其他 AGV、结构件以及最重要的工人发生碰撞。这种非接触式环境感知方法符合当前的安全法规和无人驾驶工业卡车的安全规定。然而，障碍物检测仅限于平行且靠近地面的二维平面，无法检测到 AGV 路径上的突出或悬挂物体。为了避免与这类物体发生碰撞，PAN-Robots 的想法是通过基于全向立体摄像机的 3D 感知系统来增强现有的 2D 安全性。本文介绍了 PAN-Robots 项目中实施的多层次机载传感器数据融合策略。被跟踪和分类物体的融合信息不仅可用于车载风险评估和紧急避撞，还可传输到全球控制中心，用于先进的车队协调和智能 AGV 导航。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

2015 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)

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