<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

        Select your location:

        Location

        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 September 2024
        Imagine
        Reading Time: 2 min.

        ‘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.

        About the author
        Teresa Scheunert
        Spokesperson Business KUKA 

        More about Teresa Scheunert
        Next article
        主站蜘蛛池模板: 动漫AV纯肉无码AV电影网| 久久国产精品99精品国产987| 国内精品久久久久久无码不卡 | 99中文在线精品| 亚洲第一av| 精品人妻一区二区三区蜜臀| 天天成人综合| 中日韩精品视频一区二区三区| 丰满少妇高潮在线播放不卡| 极品美女自拍偷精品视频| 综合色区亚洲熟女妇p| 久久国产精品超级碰碰热| 中文字幕av一区二区三区人妻少妇| 亚洲18禁| 男女毛多水多亚洲| 污视频在线观看网站| 美女人妻激情乱人伦| 熟女丝袜勾引一区| 熟女嫩穴?播放| 国产精品日韩av在线播放| 影音先锋资源在线| 999国内精品视频免费| 日韩中文字幕在线视频| 无码日韩做暖暖大全免费不卡| 国产成人精品永久免费视频| 国产精品午夜福利精品| 国产粉嫩学生高清专区麻豆| 国产精品一区二区婷婷| 国内永久福利在线视频图片| 野花香视频在线观看免费高清版| 国产欧美日韩精品一区二区三区| 亚洲综合色在线观看一区二区| 习水县| 99福利性视频日韩| 婷婷伊人綜合中文字幕小说| 口爆视频| 18禁网站免费无遮挡无码中文| 亚洲国产成人精品91久久久| 久久精品国产精品亚洲蜜月| 丁香五月亚洲综合深深爱| 老王av|