<sub id="for6y"><s id="for6y"><form id="for6y"></form></s></sub>

    <cite id="for6y"></cite>

        <s id="for6y"></s>
        亚洲一品道一区二区三区,国产无套粉嫩白浆在线,51妺嘿嘿午夜福利,人人妻人人澡人人爽人人精品av,欧美一区二区三区欧美日韩亚洲,欧美一本大道香蕉综合视频 ,884aa四虎影成人精品,国产精品久久久久久福利69堂

        Konumunuzu se?in:

        Konum

        In action with two arms

        A pizza chef who skilfully pulls dough into shape with both arms; a goldsmith who places tiny stones or a carpenter who uses a wide variety of tools to build a unique piece of furniture: Our human dexterity and flexibility are amazing. Robots cannot yet match these skills. But with the help of AI technologies, they should become more flexible and adaptable - and thus open up new possibilities for industrial production.


        Teresa Scheunert
        18 Eylül 2024
        Imagine
        Okuma süresi: 2 dakika

        ‘The robot programming we have known for decades is not designed for flexible production,’ explains Martin Feustel. ‘It works for thousands of identical parts, but for small batch sizes you need more flexible solutions that adapt to the environment and the process.’ To achieve this, he is working as technical project lead in the EU research project SMARTHANDLE at KUKA's Technology and Innovation Centre.

        The aim of the project is to develop technologies with AI-based components in order to automate industrial production more adaptably and efficiently. A fundamental aspect of this is how robots can grip bulky parts or unknown workpieces intelligently and reliably. How can multi-arm robot systems be used without too much programming effort? This is not about dry research theory. Industrial companies from Greece and Belgium are contributing practical use cases to the project. The team, consisting of Sebastian Geier, Sebastian Jablonski, Dr Dominik Joho, Dr Neil May, Giuseppe Monetti, Martin Feustel and project manager Dr Kirill Safronov, is developing technological solutions for these real-life use cases.

        Scenario 1: Securely gripping bulky aluminium bars

        Perfectly synchronised, the two cobots grip the long aluminium bar and slowly lift it into the air. Normally, controlling a multi-armed robot system is a complex programming challenge and harbours risks. For example, the sensitive component could crack due to non-synchronised movements. ‘You need compliant robots for simultaneous movements,’ explains Dr Kirill Safronov, observing the two robot arms as they grip the workpiece perfectly, no matter where it is - as long as it is within reach of the robot arms.

        This is made possible by innovative movement algorithms and gripping planning using machine learning. It is no longer necessary to first programme robots and then adapt the workpiece. Instead, the two-arm robot system aligns itself with the workpiece and can easily and flexibly take on industrial tasks, from handling bulky aluminium parts, which would otherwise require a large robot and several grippers, to handling slack parts such as cables or foils.

        Scenario 2: Dismantling car batteries

        Right next door, two cobots are working together to unscrew various screws from a metal block. The goal: to dismantle a complex product such as an old car battery. The challenge: the robots have to handle a wide variety of screws, some of which are dirty or rusty. This has not yet been possible with existing technologies. However, a vision system and AI technologies give the two robot arms more dexterity and flexibility and make it possible to automate such a complex task.

        What is currently successful in simulation and research environments could find its way onto factory floors in a few years' time - and ensure that automation is also worthwhile for smaller quantities, changing workpieces or recycling tasks. ‘We are moving into areas where technology is still in its infancy,’ says Dr Kirill Safronov. ‘Our aim is to advance automation and make more possible with robots.’ And in the end, more skilful and flexible robots will also relieve us human employees, especially when it comes to monotonous or dangerous tasks.

        Sonraki makale
        主站蜘蛛池模板: 中文字幕第55页一区| 各种少妇正面着bbw撒尿视频| 国产女同一区二区在线| 69精品无人区国产一区| 囯产精品久久久久久久久久妞妞| 6080YYY午夜理论片久久| 麻豆成人精品国产免费| 亚洲国产精品高清久久久| 久久精品国产久精国产果冻传媒| 日韩久久中文| 天天摸天天做天天爽天天弄| 成人国产亚洲精品天堂AV| 亚洲欧美日韩在线不卡| 日本丰满少妇xxxx| 国产va免费精品观看精品| 中国熟妇毛多多裸交视频| 日韩AV一区二区三区| 国产欧美丝袜在线二蜜芽TV| JIZZJIZZJIZZ亚洲日本| 国内精品人妻无码久久久影院导航 | 肥女五十路| 日韩中文字幕在线| 日韩有码av中文字幕| 无码一区二区三区免费看| 日日噜噜夜夜狠狠久久无码区| 久久精品中文字幕| 久久精品日韩av无码| 久久久综合香蕉尹人综合网| 不卡在线播放一区二区三区| 久久久久无码精品国产不卡| 高清破外女出血AV毛片| 97国产揄拍国产精品人妻| 图片区偷拍区小说区五月| 中文字幕久久久| 任我爽精品视频在线播放| 国产精品久久九九99九九99| 国产精品亚洲丝袜专区| 国产AV成人一区二区三区| 国产精品日韩中文字幕熟女| 亚洲无码一区二区三区蜜桃| 越西县|