Department of Applied Informatics, Automation and Mechatronics, Faculty of Mechanical Engineering, Slovak University of Technology in Bratislava, 81231 Bratislava, Slovakia.
Sensors (Basel). 2021 Apr 1;21(7):2419. doi: 10.3390/s21072419.
Human-robot collaboration is becoming ever more widespread in industry because of its adaptability. Conventional safety elements are used when converting a workplace into a collaborative one, although new technologies are becoming more widespread. This work proposes a safe robotic workplace that can adapt its operation and speed depending on the surrounding stimuli. The benefit lies in its use of promising technologies that combine safety and collaboration. Using a depth camera operating on the passive stereo principle, safety zones are created around the robotic workplace, while objects moving around the workplace are identified, including their distance from the robotic system. Passive stereo employs two colour streams that enable distance computation based on pixel shift. The colour stream is also used in the human identification process. Human identification is achieved using the Histogram of Oriented Gradients, pre-learned precisely for this purpose. The workplace also features autonomous trolleys for material supply. Unequivocal trolley identification is achieved using a real-time location system through tags placed on each trolley. The robotic workplace's speed and the halting of its work depend on the positions of objects within safety zones. The entry of a trolley with an exception to a safety zone does not affect the workplace speed. This work simulates individual scenarios that may occur at a robotic workplace with an emphasis on compliance with safety measures. The novelty lies in the integration of a real-time location system into a vision-based safety system, which are not new technologies by themselves, but their interconnection to achieve exception handling in order to reduce downtimes in the collaborative robotic system is innovative.
由于其适应性，人机协作在工业中变得越来越普遍。在将工作场所转换为协作场所时，会使用传统的安全元素，尽管新技术越来越普及。这项工作提出了一个安全的机器人工作场所，它可以根据周围的刺激来调整其操作和速度。其优点在于使用了结合安全性和协作性的有前途的技术。使用基于被动立体原理运行的深度相机，在机器人工作场所周围创建安全区域，同时识别在工作场所周围移动的物体，包括它们与机器人系统的距离。被动立体使用两个颜色流，能够根据像素移位进行距离计算。颜色流也用于人体识别过程。人体识别使用预先为此目的学习的定向梯度直方图来实现。工作场所还配备了用于材料供应的自主推车。通过放置在每个推车上的标签，使用实时定位系统实现了明确的推车识别。机器人工作场所的速度及其工作的停止取决于安全区域内物体的位置。带例外的推车进入安全区域不会影响工作场所的速度。这项工作模拟了机器人工作场所可能发生的个别情况，重点是遵守安全措施。新颖之处在于将实时定位系统集成到基于视觉的安全系统中，这些系统本身并不是新技术，但它们之间的互联实现了异常处理，以减少协作机器人系统的停机时间，这是创新的。
