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In-situ elastic calibration of robots: Minimally-invasive technology, cover-based pose search and aerospace case studies

航空航天 封面(代数) 机器人 校准 原位 航空航天工程 计算机科学 人工智能 工程类 遥感 机械工程 地质学 物理 气象学 量子力学
作者
Bruno Monsarrat,Julien-Mathieu Audet,Yves Fortin,Gabriel Côté,Michael Vistein,Lars Brandt,Ahmad Sadek,Florian Krebs
出处
期刊:Robotics and Computer-integrated Manufacturing [Elsevier]
卷期号:89: 102743-102743 被引量:2
标识
DOI:10.1016/j.rcim.2024.102743
摘要

This paper presents a novel technology for the in-situ robot elastic calibration (IREC) in industrial settings. It was especially formulated for robots that are used for accuracy demanding processes involving an exchange of force between the robot and the processed part. The calibration method was developed to conciliate requirements of minimal invasiveness, for seamless deployment in industrial settings, together with a high degree of coherence with the spectrum of action of the robot in production. The method relies on the achievement of a set of controlled load cases exerted in tribologically resisted directions after the robot is engaged against a constraint in order to establish accurate force–displacement relationships. A minimal set of engagement poses is efficiently determined using a new pose search technique involving a metric cover-based approximation heuristics applied on the surface of the constraint. The calibration apparatus and method are presented through the lens of accuracy competency development charts (Codecs), the graphical outputs of a repeated cross-validation algorithm. This new monitoring tool allows visualizing how the accuracy of deviation under load prediction grows during the calibration as a function of the number and distribution of calibration poses, and how this growth is influenced by the complexity of the load cases and that of the elastic model. Two case studies are presented to highlight both the efficiency and generality of the proposed method and algorithms, first the robotized automated fiber placement (AFP) processing of a 3D thermoplastic aerostructure and subsequently the robotized machining of a representative primary aluminium aerospace part. In these applications, the mean deviations were reduced respectively by 89.30 % and 83.08 %, allowing the achievement of the desired process tolerances.

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