Self-Adaptive Technologies for Upgraded Reconfigurable Neural computing – SATURN

We follow a bio-inspired approach based on cognitive and neural mechanisms. The method is applied to the domain of artificial vision in the case of mobile robotics.

A simulator of self-organizing maps has been developped in order to analyze the dynamics of the architecture.

Prototyping of the system onto FPGA devices.

Laurent Rodriguez, Imen Kalboussi, Benoit Miramond, Bertrand Granado: Embodied Computing: Self-adaptation in bio-inspired reconfigurable computing. RAW 2011: 1-2
Laurent Rodriguez, Jérôme Fellus, Benoit Miramond: Self-organization of reconfigurable processing elements during mobile robots missions. ReCoSoC 2011: 1-2

For last few years, evolution of SoC and increasing density of integration has proposed to target the constraints of performance, consumption and design cost/time by inter-connecting a growing number of IP blocks. This complexity added to the increasing heterogeneity of these architectures leads us today to imagine new architectural and computation models more autonomous and more easy to design.
The SATURN project (Self-Adaptive Technologies for Upgraded Reconfigurable Neural architectures) takes place in this context of autonomous embedded systems and proposes to revise the actual fundamentals of embedded computing architectures. We propose in this project an original approach compared to the classical centralized approaches based on new computation paradigms. The SATURN project associates researchers from digital embedded systems and artificial intelligence in order to define this architecture of a new type for smart embedded platforms. This architecture will be based on a totally distributed control (decentralized), thus more flexible and more robust to unpredicted changes in the system, and its environment, dynamics. Moreover, the system will be doted of self-organization capabilities allowing the dynamic allocation of computation, memory and communication resources. In order to reach these goals, the project will initiate new research activities and studies on bio-inspired mechanisms applied to digital integrated circuits.
The project will be organized as follows: the first phase will define the bare mechanisms for the self-organization of basic computation units, the second phase will develop and analyze simulation models of a first architecture specification. Finally, the last project phase will validate the approach by prototyping the system onto FPGA circuit and by using their dynamic and partial reconfiguration capabilities to demonstrate hardware self-adaptation. The concepts will be validated on a stereoscopic vision application for mobile robots.