<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

        KUKA Innovation Award 2021

        The winners of the KUKA Innovation Award 2021 have been announced: The Belgian research team Chorrobot convinced the jury with its innovative concept to automate demanding two-handed tasks and won the popular innovation competition on the topic of artificial intelligence.


        Innovation Award 2021: Artificial Intelligence Challenge

        By adding artificial intelligence to existing robot systems, the aim is to revolutionize the way humans and robots work together. This competition therefore focused on new use cases in which robots have so far faced major challenges in interacting with their real environment. Among the numerous applications for the tender on the subject of AI, an international jury of experts selected the five best concepts. To enable the finalists to realize these concepts KUKA was providing them with a sensitive lightweight robot LBR iiwa and a 3D vision sensor from Roboception free of charge and they also received coaching from KUKA experts throughout the competition.

        At the HM Digital Edition, which was broadcast entirely digitally due to the coronavirus pandemic. An international jury selected the winner of the award during Hannover Messe 2021. The winner of the 20,000 euro KUKA Innovation Award 2021 is the Belgian team „Chorrobot“ of Belgium’s Katholieke Universiteit Leuven and Flanders Make@KU Leuven.

        KUKA Innovation Award - The Challenge of Artificial Intelligence

        The Winner

        Team Chorrobot (CHallenging bimanual Operations using Reactive ROBOT control) KU Leuven and Flanders Make@KU Leuven, Belgium

        The goal of Chorrobot from Belgium’s Katholieke Universiteit Leuven and Flanders Make@KU Leuven is to leverage artificial intelligence in order to enhance the productivity of car manufacturers as well as small and medium-sized enterprises by facilitating and expediting the deployment of bimanual robot manipulation tasks. The concept enables users without extensive expertise in robotics to demonstrate some aspects of the task and to intuitively specify other aspects via a graphical user interface. This approach facilitates the commissioning of challenging bimanual tasks – including fixtureless assembly operations that involve non-rigid and non-fixed elements – as well as bimanual inspection operations in unstructured environments. 

        Team contact: Dr. Cristian Vergara

        Team Chorrobot

        The finalists

        Team ARAS (Advanced Robot Assistance Solution) Brandenburg University of Technology Cottbus-Senftenberg, Germany

        Implicit knowledge instead of complex programming codes: the goal of the team from the Brandenburg University of Technology Cottbus-Senftenberg is intelligent robot programming based on manual manufacturing sequences. The individual process steps are recorded by means of innovative data gloves and reproduced on the industrial robot using an AI-based self-learning system. The operator is freed from the need to formulate explicitly what the task is and how the robot has to perform it. Instead, the implicit knowledge of the operator during the manual manufacturing process is accessed. A corresponding skill sequence is automatically generated with this information, and the robot carries out its task – without the need to write a single line of code.

        Team contact: Marlon Lehmann

        Team ARAS

        Team BlindGrasp - IISc & MIT, India & USA

        Humans can often easily explore closed spaces with their hands and pick up objects without even looking. The application by the international team of researchers from the Indian Institute of Science and the U.S. Massachusetts Institute of Technology aims to bring such capabilities to robots. The goal is for robots to explore, recognize and pick up objects in vision-denied environments using the sense of touch. To this end, the BlindGrasp team is designing a novel gripper with tactile sensing capabilities that gathers the contact and proximity information. This data, coupled with the force-sensing capabilities of KUKA’s lightweight robot LBR iiwa, is used by a machine learning agent to learn motion policies and thus safely explore the environment and pick up objects.

        Team contact: Achu Wilson

        Team BlindGrasp

        Team CHRIS (Collaborative Human-Robot Intelligent System) A*STAR Institute for Infocomm Research (I²R), Singapore

        Particularly during the COVID-19 pandemic, collaborative robots could help to reduce human-to-human interaction. However, configuring these machines for a set of given tasks still requires a great effort. The team from the A*STAR Institute for Infocomm Research in Singapore is developing a programming-free approach that leverages the latest developments in AI capabilities. The technology enables more natural and safer human-robot collaboration. This allows the robot to support operators, especially in a high-mix low-volume manufacturing environment. The concept from Team CHRIS is comprised of intuitive object and task teaching, activity understanding as well as multimodal perception (vision, touch and speech) and reasoning. 

        Team contact: Joo Hwee Lim

        Team CHRIS

        Team CRC (Cloud Remote Control) Chair for Individualized Production RWTH Aachen University & Robots in Architecture Research, Germany

        The COVID-19 pandemic and social distancing are increasing the reliance on remote work. However, the impact of online tools for the construction industry is limited. Team CRC from the Chair for Individualized Production / RWTH Aachen University & Robots in Architecture Research is therefore integrating automation technology into online collaboration. Cloud Remote Control enables users to run robots, monitor processes and adapt tool paths from the comfort of their home or international office. This increases accessibility to worldwide robotic production, adding layers of Industrie 4.0 device communication and artificial intelligence to path planning. In this way, Cloud Remote Control empowers teams to remain safely at a distance while still collaborating closely on automated construction.

        Team contact: Ethan Kerber

        Team CRC

        AI and machine learning, especially in combination with robotics, open up a wide range of new possibilities and new fields of application - so there's a lot of potential for KUKA. That's why this year's KUKA Innovation Award was all about artificial intelligence. And we received impressive concepts from all over the world.

        Dr. Kristina Wagner, Vice President Corporate Research & Director RoX Program | The Robot X-perience

        About the KUKA Innovation Award

        In 2014, KUKA launched the Innovation Award to drive innovation in robot-based automation and promote technology transfer from research to industry. It addresses developers, graduates and research teams of companies or universities. The participants develop ideas for a task specified by KUKA. The focus is on a different technology each year. An international jury of experts selects the finalists from all the submitted applications. These final teams implement their projects with the aid of KUKA robots and other technologies and present the results to a wide audience at a trade fair. Thereby, KUKA enables them to make a professional trade fair appearance at large, international trade fairs such as the Hannover Messe, the automatica or the MEDICA medical trade fair. At the end of the trade fair week, the jury of experts chooses the winner of the prize, who receives 20,000 euros.

        主站蜘蛛池模板: 亚洲一区亚洲天堂| 国内成人综合| 无码人妻丝袜在线视频| 国产精一区二区黑人巨大| 亚洲专区视频| 国产特色一区二区三区视频| 色综合久久88色综合天天| 人妻少妇精品免费无码专区v| 国产成人精品国产成人亚洲| 国产制服丝袜在线视频| 中文字幕亚洲天堂| 国产AV天堂无码一区二区三区| 精品国产亚洲区久久露脸| 天天摸夜夜添狠狠添婷婷| 日韩精品视频2区| 91狼友社| 久久综合伊人| 91福利一区福利二区| 精品一区二区三区在线观看视频| 99er热精品视频| 377P欧洲日本亚洲大胆| 亚洲AV无码久久精品不卡| 国产香蕉国产精品偷在线观看| 日日躁狠狠躁狠狠爱| 亚洲无人区一码二码三码| 国产做a爱片久久毛片a片高清| 亚洲综合色中文网| 香蕉久久久久成人麻豆AV影院| 自拍偷怕| 国内精品久久久久影院薰衣草| 口爆少妇在线视频免费观看| 91亚色| 欧美色人妻| 精品中文字幕一区二区三区四区| 人妻少妇精品中文字幕| 国产亚洲精品VA片在线播放 | 一区二区三区午夜视频在线观看| 免费簧网站永久在线播放国产| 少妇激情一区二区三区视频小说| 中文字幕亚洲综合第一页| 3p视频在线|