<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: 亚欧美国产色| 人妻无码久久精品| 亚洲国产中文乱| 欧美综合一区二区三区| 成人啪精品视频网站午夜| 伊人二区| 亚洲男人的天堂 aⅴ无码| 66亚洲一卡2卡新区成片发布| 久久香蕉超碰97国产精品| 欧美性猛交xxxx免费看| 亚洲欧美日韩在线码| 国产精品扒开腿做爽爽爽视频| www.色五月| 亚洲中文av| 国产精品污双胞胎在线观看| av天堂午夜精品一区| 中文字幕AV无码一区二区蜜芽三区 | 欧美人与禽ZoZ0| 国产人妻熟女呻吟在线观看| 五月花成人网| 熟女色导航| 成人精品视频一区二区三区尤物| 欧美成人精品手机在线| 国内精品大秀视频日韩精品| 国内免费av在线播放| 天天久久综合| 日韩一区二区在线看精品| AV在线无码| 中文字幕人妻中出制服诱惑| 韩国青草自慰喷水无码直播间| 四季AV一区二区夜夜嗨| 日韩精品 在线 国产 丝袜| 人妻社区| 亚洲一区av| 美女成人网站| 韩国三级Hb久久精品完美| 精品久久久久久无码免费| 国产精品中文字幕自拍| 欧美777| 天天做天天爱天天高潮| 亚洲撸一撸|