Article ; Online: Safety considerations for autonomous, modular robotics in aerospace manufacturing.
2022 Volume 9, Page(s) 1024594
Abstract: Industrial robots are versatile machines that can be used to implement numerous tasks. They have been successful in applications where-after integration and commissioning-a more or less static and repetitive behaviour in conjunction with closed work ... ...
| Abstract | Industrial robots are versatile machines that can be used to implement numerous tasks. They have been successful in applications where-after integration and commissioning-a more or less static and repetitive behaviour in conjunction with closed work cells is sufficient. In aerospace manufacturing, robots still struggle to compete against either specialized machines or manual labour. This can be attributed to complex or custom parts and/or small batch sizes. Here, applicability of robots can be improved by enabling collaborative use-cases. When fixed protective fences are not desired due to handling problems of the large parts involved, sensor-based approaches like speed and separation monitoring (SSM) are required. This contribution is about how to construct dynamic volumes of space around a robot as well as around a person in the way that their combination satisfies required separation distance between robot and person. The goal was to minimize said distance by calculating volumes both adaptively and as precisely as possible given the available information. We used a voxel-based method to compute the robot safety space that includes worst-case breaking behaviour. We focused on providing a worst-case representation considering all possible breaking variations. Our approach to generate the person safety space is based on an outlook for 2D camera, AI-based workspace surveillance. |
|---|---|
| Language | English |
| Publishing date | 2022-11-18 |
| Publishing country | Switzerland |
| Document type | Journal Article |
| ZDB-ID | 2781824-X |
| ISSN | 2296-9144 ; 2296-9144 |
| ISSN (online) | 2296-9144 |
| ISSN | 2296-9144 |
| DOI | 10.3389/frobt.2022.1024594 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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