Course language is German. 6 ECTS. The module is a M.Sc. course and will be offered in winter semester. For further information, please contact Jan Stührenberg (jan.stuehrenberg(at)tuhh.de).
The project-based course starts with a general introduction to automation and robot technologies deployed to modernize the construction sector. After illuminating the current state of the art, the focus will be placed on potential use cases and benefits of quadruped robots with integrated sensors. Fundamentals of hardware systems (Arduino, Raspberry Pi) and software systems (Linux, Python, Robot Operating System (ROS)) commonly used in this field will be explained. The course provides insights into three focus areas around the use of quadruped robots, (i) exploration of locomotion mechanisms, (ii) navigation using the SLAM (Simultaneous Localization and Mapping) method, and (iii) application-related image processing techniques. Upon introducing the three focus areas, the students will form three respective groups. Each group will be assigned a project, in which the students will be given a "mIDOG", i.e. a small, quadruped robot, and use it to find a solution to a real-world problem. Also, simulation-based projects may be conducted. The background and results of each project will be documented in a paper and presented. Application examples of the last semester include robot localization by detecting fiducial tags using cameras mounted on our mIDOGs and, more specifically, tag following, platooning, BIM-based localization, and capacitive sensor grid localization.
- Introduction: Robotics in civil engineering
- Presentation and discussion of course contents
- Programming of algorithms in Python
- Application of software systems: LINUX distribution, ROS, CloudCompare
- Application of hardware systems: mIDOG, Raspberry Pi, Arduino, sensing
- mIDOG implementation and lab tests: Locomotion, use of sensors (camera, infrared sensors, accelerometers), data structures/data acquisition, programming
- Building inspection: Geodetic evaluation, image processing, localization