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Vision platform for mobile intelligent robot based on 81.6 GOPS object recognition processor

DongHyun Kim, Kwanho Kim, Joo-Young Kim, Seungjin Lee, Hoi‐Jun Yoo

Year
2008
Citations
3

Abstract

To enable power-efficient object recognition of mobile intelligent robots, 81.6GOPS object recognition processor is proposed. Based on analysis of Scale Invariant Feature Transform (SIFT) algorithm, architecture of the proposed processor is designed to support both task and data level parallelism. 10 Processing Elements (PEs) are integrated for task parallelism, and each PE is equipped with SIMD instruction for data parallelism as well. In addition, Visual Image Processing memory replaces complex local maximum pixel search operation with a single read operation for further performance gain. With the proposed processor, we also realized vision platform for real-time SIFT computation of mobile robots. The chip operation is tested up to 200MHz and consumes 540mW in the vision platform at 1.8V supply voltage and 100 MHz operation frequency.

Keywords

Computer scienceScale-invariant feature transformSIMDCognitive neuroscience of visual object recognitionMobile robotData parallelismRobotArtificial intelligenceParallel processingComputation

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