Safety considerations for autonomous, modular robotics in aerospace manufacturing - Walter, Christoph; Bexten, Simone; Felsch, Torsten; Shysh, Myroslav; Elkmann, Norbert (Frontiers in Robotics and AI, 2022)
Industrial robots are versatile machines that can be used to implement numerous tasks. However, they have been primarily successful in applications where – after integration and commissioning – a more or less static and repetitive behaviour in conjunction with individually simple tasks in conjunction with closed work cells is sufficient. In other application areas, robots struggle to compete against either specialized machines or manual labour. This is true for complex or custom parts and/or small batch sizes like we see in in aerospace manufacturing. This is, however, not a so much a limitation of robot hardware but more of the methods and software implementations controlling and complementing the robot. This includes applications where a collaborative situation develops due to constraints put into place by the overarching manufacturing concept and where fixed protective fences are not desired due to handling problems of the large parts involved. In this contribution we present a multi-step approach to safety space generation separating robot and human. For robot safety space we focus on providing a worst-case voxel structure considering all possible breaking variations. For the part of the safety space surrounding a person, the capabilities of vision-based work space surveillance are taken into account. For this we provide a brief analysis of the current capabilities of machine learning based human detection and segmentation.