Skip to content
Technical University of Munich

Community

robo.innovate Hackathon 2025: Three winners awarded

Robo.Innovate, Community |

GROWBOT, ExVo, and Seal Robotics are the three winners honored at the robo.innovate Hackathon 2025. Among ten challenges, Team GROWBOT was named "Hackathon Champion" for its solution supporting robotic-assisted tree growth. ExVo was awarded for the most scalable solution, focusing on the automated unpacking of car parts in production logistics. Finally, SEAL Robotics received recognition for the best problem-solving approach, aiming to automate the securing of shipping containers.

The robo.innovate Hackathon 2025 gathered participants to address industry challenges in robotics, AI, and IoT. Held from March 17-20 at Munich Urban Colab, the event brought together students from diverse fields, working on solutions presented by industry and academic challenge hosts. With over 100 participants, teams competed for cash prizes, evaluated on business value, market demand, technical feasibility, scalability, and novelty.

 

The Hackathon Champions: Automated Care for Forest Management

The team GROWBOT received €2,500 and the title of Hackathon Champion for their work on Challenge 04 by MIRMI AI and Robotics. They developed a robot-assisted solution for tree growth optimization designed to improve tree care through data collection and automated intervention. Their autonomous robot gathers images, tests soil conditions, and administers water and fertilizer. A connected platform controls the robot, automates actions, and visualizes data to support plant-specific treatment. Their system integrates AI-driven decision-making and a real-time database to support reforestation efforts.

ExVo (Skalierbarste Lösung)
SEAL Robotics (Beste Problem-Lösungs-Passung)

Most Scalable Solution: Automated Unpacking for Production Processes

The team ExVo (Extract. Evolve) won €1,500 for "The Most Scalable Solution" in Challenge 02 by BMW. Their project presented an innovative robotic system for automating the unpacking of car parts in production logistics. Utilizing a Franka robotic arm, a vision system, and machine learning-based pinch point detection, EXVO offered a modular, scalable unpacking solution. Their Robot-as-a-Service (RaaS) model was designed to improve production efficiency and flexibility, providing a promising solution for the future of industrial automation.

 

Best Problem-Solution Fit: Container Securing with Robotics

The team SEAL Robotics received €1,000 for "The Best Problem-Solution Fit" in Challenge 08 by SEAL Robotics. Their project aimed to automate the securing of sea freight containers, addressing labor shortages in port operations. Their system included four custom gripper solutions and a computer vision pipeline to identify and locate corner castings in a video feed. The approach combines AI-based perception and a lightweight robotic system for container handling.

To the jury: Industry experts included Robert Vogel (Sales & Business Development Manager at TQ RoboDrive), Dr. Katharina Hertkorn (Former Managing Board Member at Startup Netleaf and Robotics Expert), and Milad Malekzadeh (Head of Artificial Intelligence at NEURA Robotics). Representing the academic side were Prof. Dr. Lorenzo Masia (Executive Director of MIRMI/TUM and Professor for Intelligent Bio-Robotic Systems) and Prof. Alexander König (Professor for Robotics and Systems Intelligence at TUM).

 

Additional Information

Website: https://roboinnovate.mirmi.tum.de/roboinnovate-hackathon-2025/

Contact: 

Nicole Ebner, Managing Director of robo.innovate: nicole.ebner(at)tum.de

Arne Rost, Managing Director of TUM Venture Lab Robotics / AI: arne.rost(at)unternehmertum.de

 

Links:

◄ Back to: Community
To top

Google Custom Search

We use Google for our search. By clicking on „enable search“ you enable the search box and accept our terms of use.

Information on the use of Google Search