Development of Biomechanical Response Curves for the Calibration of Biofidelic Measuring Devices Used in Robot Collision Testing.

Collaborative robots (cobots) can be employed in close proximity to human workers without safety fences. The operation mode Power and Force Limiting requires that cobots not exceed the biomechanical limits of ISO/TS 15066 to ensure protection against injuries caused by collisions with them. Collision tests must be performed to prove that cobots cannot exceed the biomechanical limits. Such tests are performed with a biofidelic measuring device that measures contact forces and replicates the biomechanics of the human body. Biomechanical response curves serve as a reference for the calibration of such devices. In order to be able to compare measurements and limits correctly and reliably, the limits and response curves for calibration must be obtained from the same data with the same methodology. In this article, we present a new technique for developing biomechanical response curves, which employs a statistical model we used to calculate biomechanical limits for cobots in a previous study. This technique's development process entails normalizing the data over force, resampling them and then fitting the newly obtained samples to a log-normal distribution. The statistical model makes it possible to produce response curves for the same quantile we used for the limits. Our technique adds a confidence region around each response curve to express the sufficiency of the available data. We have produced response curves for 24 different body locations for which we have calculated limits. These curves will enable manufacturers of cobot testing equipment to calibrate their measuring devices precisely.

Automated disassembly of e-waste-requirements on modeling of processes and product states.

Automated disassembly is increasingly in focus for Recycling, Re-use, and Remanufacturing (Re-X) activities. Trends in digitalization, in particular digital twin (DT) technologies and the digital product passport, as well as recently proposed European legislation such as the Net Zero and the Critical materials Acts will accelerate digitalization of product documentation and factory processes. In this contribution we look beyond these activities by discussing digital information for stakeholders at the Re-X segment of the value-chain. Furthermore, we present an approach to automated product disassembly based on different levels of available product information. The challenges for automated disassembly and the subsequent requirements on modeling of disassembly processes and product states for electronic waste are examined. The authors use a top-down (e.g., review of existing standards and process definitions) methodology to define an initial data model for disassembly processes. An additional bottom-up approach, whereby 5 exemplary electronics products were manually disassembled, was employed to analyze the efficacy of the initial data model and to offer improvements. This paper reports on our suggested informal data models for automatic electronics disassembly and the associated robotic skills.

Safety considerations for autonomous, modular robotics in aerospace manufacturing.

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.