The teams of upCAT#6

Philipp Hauff

POS Food Recognition
Team: Felix Schweikardt und Julian Herrmann

Brief description of the business idea:
We offer cafeterias and company restaurants a risk-free and uncomplicated increase in efficiency by automating the checkout process. The goal here is to optically detect the tablet during the checkout process and thus evaluate the customer’s meal choice with the help of machine learning algorithms. This can significantly reduce waiting times and costs at checkouts.


Short description about the team:
We, Felix and Julian, are both Machine Learning enthusiasts and industrial engineers interested in founding a company, shortly before graduating with a Master’s degree from KIT. By participating in upCAT, we would like to challenge our business idea, benefit from a network of experienced experts, and acquire best practices for a startup in workshops. We hope that this will help us to move our whole idea forward faster.

Team: Dr. Samuel Braun und Dr. Gregor Olenik

Brief description of the business idea:
We enable specialized flow simulations that are not feasible with current commercial methods, as there is no corresponding software on the market yet. We provide our customers with a tool to analyze existing components in detail and to optimize designs even before the prototype phase with minimal time expenditure. We work closely with our customers on projects and rent cloud-based simulation services.

Brief description about the team:
We are two mechanical engineers who graduated from KIT. Together we have over 10 years of experience in the field of flow simulation and scientific computing. Our goal is to build an established company in the field of flow simulation within the next 5 years.

By participating in upCAT#6, we hope to learn methods that will allow us to approach the challenges of starting a business in a structured way.

Team: Dr. Uwe Bog und Dr. Jahn Krimpmann

Brief description of the business idea:
We have developed a micro/nano printer that flexibly implements various processes for the generation of micro- and nanostructures with several different substances and makes them available to users in an automated and easy-to-use manner. Especially the processing of sensitive biological materials is possible here due to mild process parameters and opens up the generation of corresponding surface patterns to users with a biological and biomedical background without having to have special expertise in the printing technique itself. In addition, we offer kits with consumables and other services based around the printer that allow our customers to focus on their questions instead of generating the required structures.

Brief description about the team:
Dr. Bog is a co-inventor and principal developer of the microprinter platform. His background as an electrical engineer and his postdoctoral work in the field of device functionalization using scanning probe lithography methods give him the ideal experience to further develop the printer setup into an out-of-the-box product and to develop the planned additional printer modules.

Dr. Sekula-Neuner holds a doctorate in biology and has many years of experience with the application of technology in the life science field. She is responsible for the consumable kits and custom services in the product development department and is also an application specialist in marketing and sales in direct contact with biological research groups.

We would like to expand our knowledge on product commercialization, marketing strategies and business plans. In the end, we would like to get feedback on our business model to be better prepared for our product launch.

Team: functional_intelligence

Mastering the complexity of robot gripping systems with functional pattern recognition.

Germany as an industrial location is a technological leader in the robot gripper market and sets global trends. Motivated by Industry 4.0, the mega trend towards human-robot collaboration and the accompanying planning of innovative robot systems, the complexity and diversity of robot gripping systems is constantly increasing.

Our solution is an innovative customer communication tool for manufacturers of robot grippers and for planners of robot systems. This does not focus on the product, but on the customer task and the user. With AI algorithms that are based on task-oriented, functional models, we capture both the user task and the gripper systems

of the manufacturers and thus enable intelligent, automatic matching with integrated consistency checks. The advantages are obvious: common customer and manufacturer view, automatic early warning systems and tests, as well as much better scalability through multiplication of expert knowledge.

In a first step, we will establish our solution in close cooperation with leading manufacturers from the robotics industry. Our goal is to provide an open industry platform in the medium term that covers the entire robot gripper market.

Do you want to see more?

More blog post