Initial Study of Neuromorphic Application for Vision-Based Navigation
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- KARIYA Kazuki
- Department of Space and Astronautical Science, SOKENDAI
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- FUKUDA Seisuke
- Institute of Space and Astronautical Science, JAXA
Abstract
<p>High precision landing capability increases accessibility to scientifically interesting areas and makes a safe landing. Vision-based navigation is one of the GN&C functions to achieve that. The navigation technique requires onboard and real-time image processing algorithms performing image recognition, feature extraction, matching, tracking, etc. However, despite the demand for fast image processing task, space-grade computers have been slower than commercial ones, lagging behind them by 1-2 orders of magnitude in performance. To address the issue, we study the applicability of a vision-based navigation algorithm for crater classification in architecture of neuromorphic processor chips which are expected to operate with ultra-low power consumption. The neuromorphic processor chip operates asynchronously and in parallel mimicking neuro-biological architecture like our brain. Therefore, the processor operates as a spiking neural network (SNN). The difference in mechanisms between timing-based spiking neurons and rate-based artificial neurons has a problem of how to make the SNNs with equivalent functions as artificial neural networks (ANNs). This study proposes a method to train the SNN by transferring weights of the ANN trained specially as synaptic efficacy of the SNN, and also evaluates the accuracy and power consumption of the SNN.</p>
Journal
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- TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, AEROSPACE TECHNOLOGY JAPAN
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TRANSACTIONS OF THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES, AEROSPACE TECHNOLOGY JAPAN 18 (3), 108-115, 2020
THE JAPAN SOCIETY FOR AERONAUTICAL AND SPACE SCIENCES
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Details 詳細情報について
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- CRID
- 1390848250109487488
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- NII Article ID
- 130007840118
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- ISSN
- 18840485
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- Text Lang
- en
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- Data Source
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- JaLC
- Crossref
- CiNii Articles
- KAKEN
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- Abstract License Flag
- Disallowed