安全人机协作的机器感知平台

M. Zlatanski, P. Sommer, F. Zurfluh, Saleh Gholam Zadeh, Antonino Faraone, N. Perera
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引用次数: 6

摘要

速度和分离监测是协作机器人安全标准中定义的操作,旨在实时避免碰撞。激光扫描仪是安全认证的设备,也是这种应用的传统传感器选择。不幸的是,它们提供的目标信息数量有限,限制了它们在现实协作机器人场景中的使用,在这种场景中,需要了解被检测目标的性质。我们提出了一个基于宽带w波段雷达、3D相机和激光扫描仪的安全人机协作的机器感知平台。除了计算距离和到达角信息外,我们还利用雷达回波信号的微多普勒特征来区分人和物体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Machine Perception Platform for Safe Human-Robot Collaboration
Speed and separation monitoring, operation defined in safety standards for collaborative robots, is meant for real-time collision avoidance. Laser scanners are safety-certified devices and a traditional sensor choice for this application. Unfortunately, the limited amount of target information they provide restricts their use in realistic collaborative robot scenarios, in which knowledge about the nature of the detected targets is required. We propose a machine perception platform for safe human-robot collaboration based on a broadband W-band radar, a 3D camera, and a laser scanner. Besides computing range and angle-of-arrival information, we use the micro-Doppler signatures of the radar echo signals to distinguish between humans and objects.
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