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GRANT: Ground-Roaming Autonomous Neuromorphic Targeter

Jonathan D. Ambrose, Adam Z. Foshie, Mark E. Dean, James S. Plank, Garrett S. Rose, J. Parker Mitchell, Catherine D. Schuman, Grant Bruer

发表年份
2020
引用次数
5

摘要

In this work we describe the design, implementation, and testing of the first neuromorphic robot capable of obstacle avoidance, grid coverage, and targeting controlled by the second generation Dynamic Adaptive Neural Network Array (DANNA2) digital spiking neuromorphic processor. The simplicity of the DANNA2 processor along with the TENNLab hardware/software co-design framework allows for compact spiking networks that can run efficiently on a small, resource-constrained, platform such as a Xilinx Artix-7 field-programmable gate array. Additionally, we present the dynamic reconfigurability of DANNA2 arrays as a method of realizing complex, multi-objective tasks on hardware that is restricted to relatively small networks.

关键词

ReconfigurabilityNeuromorphic engineeringComputer scienceField-programmable gate arrayComputer architectureEmbedded systemRoamingFootprintComputer hardwareArtificial neural network

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