Organic architectures for self-organising smart pixel sensor chips

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The goal of the project pursues two directions. First, we want to expand our conceptual work on OC chip architectures and on a tool for the design of controlled emergent computing. Second, meanwhile two of our OC concepts are mature enough to demonstrate them in real applications. The superiority of emergent algorithms based on our OC concept of Marching Pixels (MP) was proven for application-specific designs. Now, these benefits shall be achieved in generic architectures. For that, we developed a programmable parallel architecture tailored for emergent computing, which shall be experimentally verified by realisation as ASIC or FPGA. MP algorithms shall be implemented on that architecture and for comparison purposes also on GPGPU many-core architectures to see if the superiority of emergent computing can also be exploited on such parallel architectures. Furthermore, the MP approach shall be expanded for configuring future nanoarchitectures. For the automatic design of MP behaviour we developed a design framework based on the evolution of Cellular Automata (CA) and Genetic Programming. To improve the quality of the framework’s evolved emergent computing scheme, we will introduce concepts for multi-evolution and eliminating of redundant CA. The generic approach of the tool to design arbitrary emergent control systems is shown for the Chemical Organization theory. The efficiency of an emergent hardwired path planning algorithm from us shall be demonstrated for the mobile robot OSCAR. Finally, our chip architecture shall exploit self-optimising features by using ASoC methods.