Secure, Autonomous and AI-Based Systems
Secure, Autonomous and AI-Based Systems
The digital transformation and expansion of cyber-physical systems increasingly require more collaborative solutions and human-machine interaction. Cognitive computing also increases the autonomy of systems (e.g. autonomous vehicles and flying objects). At the same time, it also poses challenges in communication and interface design between components and systems, data acquisition and analysis using artificial intelligence (e.g. Big Data, machine learning), and IT security.
Research in this area is conducted primarily at the Affective and Cognitive Institute (ACI), Institute for Machine Learning and Analytics (IMLA), Institute for Unmanned Aerial Systems (IUAS), and the Institute of Reliable Embedded Systems and Communication Electronics (ivESK).
| Title | ML Lokalisierung |
| Short Name | ML Lokalisierung |
| Short Description | Maschinelles Lernen für die echtzeitfähige und hochgenaue Lokalisierung mit Multisensorsystemen: Inertial Measurement Unit (IMUs) like accelerometer and gyroscopes are becoming cheaper and cheaper, as they are increasingly used in consumer applications. However, for these applications, short time stability is mostly sufficient, so that these devices show a large dependency (drift) on time and temperature. Based on previous analysis, it can be assumed that ML-based support of calibration processes might significantly improve the resulting accuracy of these low cost devices also for long-term industrial applications. It is the student’s task to analyze the results until now and to propose ML-algorithms for a “self-learning” calibration. Based on the results, experiments shall be conducted and the proposed algorithms shall be verified. |
| Year Of Acquisition | 2018 |
| Start Date | 2018-09-01 |
| End Date | 2019-08-31 |
| Project Managers | Sikora, Axel, Prof. Dr. |
| Faculties | EMI |
| Institution | ivESK |