Intelligent System Lab
Intelligent System Lab
Description
Explore the world of mobile robots—on land or water—using our cutting-edge sensors and real-world data from past field trials. Together with your team, choose the technology that matches your interests and skills. What’s in it for you? - Hands-on experience: Work with real robots and datasets. - Short lecture series: Learn the basics of robotics, computer vision, and the unique challenges of embedded systems. - Focus on object recognition: Tackle real-time detection with limited resources—energy efficiency, noisy sensors, and changing environments. - Interdisciplinary collaboration: Combine expertise from different fields to solve complex problems. As part of an ECIU student team, you’ll develop deep learning solutions to detect robots and obstacles. Select, evaluate, and fine-tune methods to make them fast, reliable, and ready for embedded platforms.
The Team
Teamchers
These are the teamchers you'll work with on the challenge.
Learners
- Study period
- 8 April – 3 July 2026
- Study format
- Hybrid
- Application period
- 5 March – 26 March 2026
- Credits
- 3 ECTS
- Hosting university
- Hamburg University of Technology
Information
Value and progress
Using deep learning methods
At the end of the micro module learner are abl to apply deep learning methods to detect other robots and obstacles.
ESCO SKILLS
Evaluating and tuning methods for object recognition on embedded systems.
At the end of the micro module learner will be able to select existing methods suitable for object detection on an embedded platform. A key aspect will be evaluating and tuning the methods to achieve sufficiently fast and reliable object detection.
ESCO SKILLS
Team work in interdisciplinary teams
By working in groups to independently define work processes, distribute tasks within the group and develop solutions collaboratively, learners should be able to assess their level of knowledge with the help of the projects and independently acquire the knowledge necessary to solve research-oriented tasks at the end of the micro module.
ESCO SKILLS
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Hosting university
Hamburg University of Technology
