Journal
SENSORS
Volume 21, Issue 4, Pages -Publisher
MDPI
DOI: 10.3390/s21041536
Keywords
wearable device; semantic segmentation; SLAM; assistance for visually impaired people; localization; semantic map
Funding
- National Natural Science Foundation of China [61873037, 61903039]
- China Postdoctoral Science Foundation [BX20190035, 2020M680015, 19H02093]
- Ministry of Education, Culture, Sports, Science and Technology of Japan
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The paper introduces a wearable navigation device integrating semantic visual SLAM and a powerful mobile computing platform, providing real-time feedback of environmental information to visually impaired individuals. Testing shows the system performs well on a wearable navigation device.
Wearable auxiliary devices for visually impaired people are highly attractive research topics. Although many proposed wearable navigation devices can assist visually impaired people in obstacle avoidance and navigation, these devices cannot feedback detailed information about the obstacles or help the visually impaired understand the environment. In this paper, we proposed a wearable navigation device for the visually impaired by integrating the semantic visual SLAM (Simultaneous Localization And Mapping) and the newly launched powerful mobile computing platform. This system uses an Image-Depth (RGB-D) camera based on structured light as the sensor, as the control center. We also focused on the technology that combines SLAM technology with the extraction of semantic information from the environment. It ensures that the computing platform understands the surrounding environment in real-time and can feed it back to the visually impaired in the form of voice broadcast. Finally, we tested the performance of the proposed semantic visual SLAM system on this device. The results indicate that the system can run in real-time on a wearable navigation device with sufficient accuracy.
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