Abstract
Embedded visual odometry(VO) implementation may provide a low-power, small-size alternative or compan-ion positioning system to the Global Navigation Satellite Systems(GNSS) and Inertial Navigation System(INS). As the em-bedded systems are memory scarce, in this paper, a new low-memory footprint neural network-based visual odometry method that is implementable on embedded systems is introduced and evaluated. To deploy the neural network, MAX78002 [1] artificial intelligence microcontroller has been chosen as the embedded platform. To the best of our knowledge, this is the first study that provides a microcontroller-based visual odometry solution.
| Original language | English |
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| Title of host publication | Proceedings - 2023 10th International Conference on Electrical and Electronics Engineering, ICEEE 2023 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 47-51 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798350304299 |
| DOIs | |
| Publication status | Published - 2023 |
| Event | 10th International Conference on Electrical and Electronics Engineering, ICEEE 2023 - Istanbul, Turkey Duration: 8 May 2023 → 10 May 2023 |
Publication series
| Name | Proceedings - 2023 10th International Conference on Electrical and Electronics Engineering, ICEEE 2023 |
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Conference
| Conference | 10th International Conference on Electrical and Electronics Engineering, ICEEE 2023 |
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| Country/Territory | Turkey |
| City | Istanbul |
| Period | 8/05/23 → 10/05/23 |
Bibliographical note
Publisher Copyright:© 2023 IEEE.
Keywords
- CNN
- Deep Learning
- Embedded System
- KITTI
- Visual Odometry