Skip to content
‹ Back to IndustriesIndustrial IoT

Artificial Intelligence Challenge: These are the finalists for the 2021 KUKA Innovation Award

KUKA has announced the five finalists for its 2021 KUKA Innovation Award, which this year centers on artificial intelligence in robotics. The selected teams were chosen by an international jury based on the strength of their AI-driven robotics concepts. The winning team will receive a monetary prize of 20,000 euros.

This story was produced through MarketScale. See how Industrial IoT teams put it to work with AI Visibility (GEO).

Promoted content from Kuka on MarketScale.

By Industrial Iot · · AiInnovation AwardKukaRobotics
Share
Artificial Intelligence Challenge: These are the finalists for the 2021 KUKA Innovation Award

Key takeaways

01

Five finalist teams were selected by an international jury for the 2021 KUKA Innovation Award.

02

The award theme focuses on artificial intelligence as a megatrend in industrial robotics.

03

The winner receives a 20,000 euro prize for their AI robotics concept.

Free workspace

Turn your Industrial IoT expertise into content.

Record interviews, organize footage, and write with AI on a free trial of the MarketScale platform for qualifying companies. No demo required, no credit card.

Try it Free

Innovations centered on the megatrend of artificial intelligence (AI): 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. A monetary prize of 20,000 euro awaits the winner.

AI is becoming increasingly important for industry – and the combination with robotics, in particular, is opening up completely new possibilities and applications.

An international jury of experts evaluated the concepts for the “Artificial Intelligence Challenge” and selected five finalists. The teams are provided with a KUKA robot free of charge and are being trained and coached by KUKA experts throughout the competition. The five finalist teams now have until the virtual Hannover Messe in April to implement their ideas. They will present their applications to a large specialist audience at the international industrial trade fair before the jury chooses the winner of the renowned competition during the fair.

These are the finalists of the Artificial Intelligence Challenge:

Team ARAS

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 BlindGrasp

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 Chorrobot

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 CHRIS

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 CRC

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.

About the KUKA Innovation Award

KUKA launched the innovation competition in 2014, focusing on different technologies each year. The goal of the award is to promote and expedite the transfer of technology from research to industry. All information about the competition as well as the topics and winners in recent years can be found here.

Kuka

Part of this channel

Kuka

Industrial robotics and automation systems for global manufacturing operations.

Visit the channel

Your experts belong here

Every story in MarketScale Industrial IoT starts with a company putting its controls engineers, plant-floor specialists, and integration partners on the record. Buyers are already reading this topic. The only question is whose experts they find.

Plant and controls buyers research deep before contact, and your engineers get to shape that research.

Book DemoSee how it works15 minutes, straight to a calendar.

About the author

II
Industrial Iot
B2B Weekly

The week in Industrial IoT, and sixteen other industries, every Monday.

Ten stories, one-line takes, five minutes. Free.

Industrial IoT: are you visible to AI?

Before they reach out, Industrial IoT buyers ask AI engines which vendors to trust. Explore how your experts, customers, and partners can become useful content for buyers and AI search.

Free Trial

You just read one Industrial IoT expert. Your company is full of them.

This article was produced through MarketScale. The same platform turns your controls engineers, plant-floor specialists, and integration partners into the articles, video, and social content Industrial IoT buyers are searching for. Start a free trial and see it with your own people. For qualifying companies, no credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What your free trial includes

Hands-on access to the MarketScale platform
Media requests to your crowd, remote recording, AI writing tools
No demo required. No credit card.
For qualifying companies. Company confirmation required.

More Industrial IoT Insights

A3's final mobile robot safety standard is written for the sites running the robots

A3's final mobile robot safety standard is written for the sites running the robots

ANSI/A3 R15.08-3-2026 is now available from A3. It completes the three-part R15.08 series for industrial mobile robot (IMR) safety. Part 3 is written for the sites that run the robots. It covers risk assessment, management of change, employee training and periodic reviews and inspections, so safety work continues in day-to-day operation after deployment.

  • 01The robot maker documents the environment a mobile robot was built for, and Part 3 makes the operating site responsible for managing changes to the environment the robot actually works in.
  • 02Part 1 was reaffirmed in 2026 with no technical changes, while Part 3 spells out what users must do to operate IMR applications safely.
  • 03Sites running fixed cells and mobile robots may use one safety program, because R15.08-3 was written alongside R15.06 Part 3.

Oct 11, 2026

Schneider's $22.6 billion PTC deal is a bet on design data for industrial AI

Schneider's $22.6 billion PTC deal is a bet on design data for industrial AI

Schneider Electric is buying PTC for $22.6 billion in cash. It is betting PTC’s design and engineering data can help deploy industrial AI for manufacturers. The deal is expected to close by the third quarter of 2027, subject to approvals from PTC shareholders and regulators.

  • 01Schneider calls the combined business open and interoperable across systems. Buyers should test that promise.

Oct 10, 2026

Matt Kelly says packaging automation pays back under two years

Matt Kelly says packaging automation pays back under two years

Matt Kelly and Joe Bradley argue brownfield warehouses often speed up picking while leaving packing manual. SupplyChainBrain reported in June 2026 that Kelly said service-model packaging projects can pay back in as little as one month and capital projects in under two years. Sparck's published 3-second boxing benchmark shows why operators still need a workflow-by-workflow comparison.

  • 01SupplyChainBrain reported in June 2026 that Kelly said some service-model packaging projects can pay back in as little as one month and capital projects in under two years.
  • 02Bradley says BoxLast can work from a license plate ID, a unique order identifier, so the machine can print and apply a shipping label without preloading weights and dimensions.
  • 03Sparck benchmarks, up to 20 stations and a box every 3 seconds, illustrate why operators must compare throughput, staffing and machine scope.

Oct 2, 2026

Explore More Industrial IoT Insights

Read more expert perspectives from across Industrial IoT.

Browse Industrial IoT Hub

About the Expert

II
Industrial Iot

For B2B teams

Your experts could be publishing here

Stories like this one run on content MarketScale captures from real practitioners. See how your team's expertise becomes coverage in Industrial IoT and beyond.

Book a Demo

Or call us. No forms required. We pick up. 214-945-2512