Two regimes permitting safe physical human-robot interaction, speed and separation monitoring and safety-rated monitored stop, depend on reliable perception of the space surrounding the robot. This can be accomplished by visual sensors (like cameras, RGB-D cameras, LIDARs), proximity sensors, or dedicated devices used in industrial settings like pads that are activated by the presence of the operator. The deployment of a particular solution is often ad hoc and no unified representation of the interaction space or its coverage by the different sensors exists. In this work, we make first steps in this direction by defining the spaces to be monitored, representing all sensor data as information about occupancy and using occupancy-based metrics to calculate how a particular sensor covers the workspace. We demonstrate our approach in two (multi-)sensor-placement experiments in three static scenes and one experiment in a dynamic scene. The occupancy representation allow to compare the effectiveness of various sensor setups. Therefore, this approach can serve as a prototyping tool to establish the sensor setup that provides the most efficient coverage for the given metrics and sensor representations.
翻译:允许安全物理人体-机器人相互作用、速度和分离监测以及安全等级监测停止的两个制度,取决于对机器人周围空间的可靠认识,这可以通过视觉传感器(如照相机、RGB-D摄像机、LIDARs)、近距离传感器或工业环境中使用的专用装置(如操作员在场时激活的垫片)实现。部署特定解决方案往往是临时性的,对互动空间或不同传感器所覆盖的空间没有统一表示。在这项工作中,我们通过界定监测的空间,代表所有传感器数据作为占用信息,并使用基于占用的测量尺度来计算特定传感器如何覆盖工作空间,从而朝着这一方向迈出第一步。我们用三种(多传感器)在三个静态场进行实验,并在动态场进行一项实验,以展示我们的方法。使用这种实验可以比较各种传感器设置的有效性。因此,这种方法可以作为一种程序化工具,用以建立传感器设置,为特定计量仪和传感器设置提供最有效的覆盖范围。</s>