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An easily implementable path solution algorithm for 2D spatial problems,based on excitable/programmable characteristics of a specific cellularnonlinear network (CNN) model is presented and numerically investigated. Thenetwork is a single layer bioinspired model which was also implemented in CMOStechnology. It exhibits excitable characteristics with regionally bistablecells. The related response realizes propagations of trigger autowaves, wherethe excitable mode can be globally preset and reset. It is shown that, obstacledistributions in 2D space can also be directly mapped onto the coupled cellarray in the network. Combining these two features, the network model can serveas the main block in a 2D path computing processor. The related algorithm andconfigurations are numerically experimented with circuit level parameters andperformance estimations are also presented. The simplicity of the model alsoallows alternative technology and device level implementation, which may becomecritical in autonomous processor design of related micro or nanoscale roboticapplications.

2D Path Solutions from a Single Layer Excitable CNN Model