KUKA Innovation Award

The finalists for the 2021 KUKA Innovation Award have been selected. Five teams convinced the international jury with their robotics concepts on the topic of AI. The winner team will be announced at the Hannover Fair Digital Edition on Thursday, April 15, and can look forward to a monetary prize of 20,000 euros. Until then, you can experience the concepts of the five finalists up close.


Learn more about the teams

Take a look at the applications of all participating teams on the KUKA iimotion video platform

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 year's competition therefore focuses 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 KUKA is providing them with a sensitive lightweight robot LBR iiwa and a 3D vision sensor from Roboception free of charge. They will also receive training and coaching from KUKA experts throughout the competition. The five final teams have until the virtual Hannover Messe in April to implement their concepts. At the HM Digital Edition (12-16 April 2021), they will present their applications to an international audience of experts and to the jury, which will select the winner of the prestigious competition within the framework of the virtual trade fair.


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 BlindGrasp

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 Chorrobot

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


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 CRC

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

At KUKA, we are looking very closely at the new prospects offered by artificial intelligence and machine learning. That’s why our innovation competition this year is also focusing on the megatrend of AI for the first time. And we received outstanding 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

The award is being presented for the eighth time. As the world's leading company in robot-based automation, KUKA has been working closely with scientists and R&D partners worldwide on various scientific and technical topics for many years. To strengthen this cooperation, the KUKA Innovation Award was launched in 2014.

The competition aims to accelerate the overall pace of innovation in the field of robot-based automation and to strengthen technology transfer from research to industry. It addresses developers, graduates and research teams of companies or universities.

Further information to the Artificial Intelligence Challenge

The applicants were asked to select new use cases in which robots today face serious challenges in interacting with their real environment. It was required that the applications cover a wide range of sectors, from manufacturing industry and agriculture to inspection, maintenance and end users. AI is becoming increasingly important for industry – and the combination with robotics, in particular, is opening up completely new possibilities and applications. By adding Artificial Intelligence to existing robotic systems, the aim is to revolutionize the way humans and robots work together.

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