Superordinate Safety System for Human Robot Interaction in Complex Industrial Environment

M. Bdiwi, Sebastian Krusche, Jayanto Halim, Steffen Ihlenfeldt
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Abstract

Various papers have focused on developing new sensors and technologies for precisely detecting the human presence in the collaborative workspace. However, an important aspect has often been overlooked. It is the context of the appearance/ disappearance of the human concerning the robot activities and workspace circumstances. In other words, which circumstances could prevent the vision system from detecting humans; have they left the cooperation workspace correctly or has a fault event happened? E.g. they are covered by another object and not visible to the camera system anymore. This investigation proposes a superordinate safety system for HRI applications. The proposed system consists of several modules. Two of them will be presented in detail in this paper. 1. “Human-robot states” module: it contains; a. The possible status of the detected and the lost objects based on their position and safety procedures (danger, safe etc.); b. the possible events which could happen for every object based on their activities and their relationship with other objects. 2. “Events classifiers” module: it analyzes the status of every new and lost object, whether it has entered or left the workspace correctly or an unexpected event has happened. The proposed approach has been tested in a dynamic experimental field with heavy-duty robot.
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复杂工业环境下人机交互的超级安全系统
各种各样的论文都集中在开发新的传感器和技术,以精确地检测协作工作空间中的人类存在。然而,一个重要的方面经常被忽视。它是关于机器人活动和工作空间环境的人的出现/消失的上下文。换句话说,哪些情况会阻止视觉系统检测人类;他们是否正确地离开了协作工作区,或者是否发生了错误事件?例如,它们被另一个物体覆盖,摄像系统再也看不到它们了。本研究提出了一种适用于HRI应用的高级安全系统。该系统由几个模块组成。本文将详细介绍其中的两种方法。1. “人-机器人状态”模块:它包含;a.根据物体的位置和安全程序(危险、安全等)判断被探测物体和丢失物体的可能状态;根据每个物体的活动和它们与其他物体的关系,每个物体可能发生的事件。2. “事件分类器”模块:分析每个新对象和丢失对象的状态,是否正确进入或离开工作区,是否发生了意外事件。该方法已在重型机器人动态试验场中进行了验证。
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