Institute of
Cognitive Integrated Sensor Systems
Prof. Dr.-Ing. Andreas König
Institute of
Cognitive Integrated Sensor Systems
Prof. Dr.-Ing. Andreas König
Integrated Sensor Systems
Dynamically Reconfigurable Sensor Electronics:
In this research the improvement of integrated sensor systems with regard to flexibility, rapid-prototyping, and self-calibration or -trimming are investigated. Inspirations are drawn from industrial standard designs, which incorporate an increasing amount of reconfigurability, and the field of evolutionary electronics and analog evolvable hardware. Architectures and algorithms for the implementation of generic sensor electronics with the self-x-properties advocated by the recent field of Organic-Computing and Cyber-Physical-Systems, are developed and assessed. There is an interesting link from these activities to circuit sizing in particular and circuit synthesis activities in general. The following projects have contributed to that line of research:
Dynamically Reconfigurable Mixed-Signal Electronics for Embedded and Intelligent Sensor Systems
Dynamically Reconfigurable Mixed-Signal Embedded Systems - Architectures and Algorithms
MEMS-DC-Relays for Dynamically Reconfigurable integrated Mixed-Signal Electronics and Systems with Self-x Properties
Distributed Wireless Integrated Sensor Systems and Networks:
In this research, the development and application of distributed wireless integrated sensor systems is pursued in the context of automation or smart environment applications. In particular, integration technology beyond straight PCB systems is pursued based on advanced packaging and related MEMS technologies for volume or 3D system assembly. From basic 3D printing, e.g., Makerbot, to proprietary technologies are applied to achieve economically feasible prototypes and application systems. Thus, the realization of multi-sensor measurement systems, including localization context determination, low-power, and self-x properties. Experience from the above described research on Dynamically Reconfigurable Sensor Electronics is put into practical use. There is a strong relation to recent activities in Cyber-Physical-Systems The following projects are contributing to that line of research:
Lab-on-Spoon Research Activity in ISE-Smart-Kitchen
E-Taster Assistance System with Lab-on-Spoon and Lab-on Fork as 'Electronic Tongues'
CMOS Imagers & Embedded Vision Systems:
In this line of research, sensors in the visual range and near infrared as well as range detection based on standard CMOS IC technologies are investigated. Improvement of image acquisition with regard to dynamic range and linearity, cost and/or minimization, as well as the computation of appropriate features in the vision sensor architecture for lean embedded vision systems, e.g., for automotive or robot vision applications, has been investigated. Biologically inspired spiking image sensor concepts have been studied and developed. More recently, the work is extended to CMOS range sensing concepts. Teaching activities on mixed-signal circuit and integrated sensor system design are closely entwined with these research activities. The following projects have contributed to the research:
OCR-Project: "Investigations on Integrated Low-Cost Image Processing and Recognition System Design''
CMOS Image Sensors with Integrated Preprocessing for Application-Specific Vision Systems
Characterization of a Custom CMOS-Technology for Image Sensor Design
3D-ToF-Camera System Design, Algorithms, and Applications
DeCaDrive - Multi-Sensor Intelligent System for On-Line Driver State and Intention Recognition
More sensor chips can be found here :
Neurocomputing Circuits & Systems:
In this line of research biomimetic sensors, circuits & systems are regarded. A focus in this work is on mimicking nervous systems and sensors of living beings by appropriate circuits microstructures. Neural hardware, in particular neuromorphic implementations but also more abstract incorporations of the underlying information processing principles are regarded in this research. There is a strong relation with the research on image sensors with integrated preprocessing or light flux to spike rate transduction. In addition of the commonly aspired features of massive parallelism and adaptivity, this research aims in particular on the exploitation of robustness features and low-power circuits for future self-x (multi) sensor systems. The research encompasses also related activities on Evolvable Hardware. There is a strong relation with teaching activities, where students are acquainted with the underlying innovative architectures, circuits, and system implementation.The following projects have contributed to the research:
Application of Neurocomputing Systems: A Joined Teaching and Research Initiative
Holistic Design of Recognition Systems (Project GAME, SPP 1076 VIVA)
