Research and Implementation of Travel Aids for Blind and Visually Impaired People
Blind and visually impaired (BVI) people face significant challenges in perception, navigation, and safety during travel. Existing infrastructure (e.g., blind lanes) and traditional aids (e.g., walking sticks, basic audio feedback) provide limited flexibility and interactivity for complex environmen...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/25/14/4518 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849419083620024320 |
|---|---|
| author | Jun Xu Shilong Xu Mingyu Ma Jing Ma Chuanlong Li |
| author_facet | Jun Xu Shilong Xu Mingyu Ma Jing Ma Chuanlong Li |
| author_sort | Jun Xu |
| collection | DOAJ |
| description | Blind and visually impaired (BVI) people face significant challenges in perception, navigation, and safety during travel. Existing infrastructure (e.g., blind lanes) and traditional aids (e.g., walking sticks, basic audio feedback) provide limited flexibility and interactivity for complex environments. To solve this problem, we propose a real-time travel assistance system based on deep learning. The hardware comprises an NVIDIA Jetson Nano controller, an Intel D435i depth camera for environmental sensing, and SG90 servo motors for feedback. To address embedded device computational constraints, we developed a lightweight object detection and segmentation algorithm. Key innovations include a multi-scale attention feature extraction backbone, a dual-stream fusion module incorporating the Mamba architecture, and adaptive context-aware detection/segmentation heads. This design ensures high computational efficiency and real-time performance. The system workflow is as follows: (1) the D435i captures real-time environmental data; (2) the processor analyzes this data, converting obstacle distances and path deviations into electrical signals; (3) servo motors deliver vibratory feedback for guidance and alerts. Preliminary tests confirm that the system can effectively detect obstacles and correct path deviations in real time, suggesting its potential to assist BVI users. However, as this is a work in progress, comprehensive field trials with BVI participants are required to fully validate its efficacy. |
| format | Article |
| id | doaj-art-ee02c4491d1c45c6849d524df26fd043 |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-ee02c4491d1c45c6849d524df26fd0432025-08-20T03:32:15ZengMDPI AGSensors1424-82202025-07-012514451810.3390/s25144518Research and Implementation of Travel Aids for Blind and Visually Impaired PeopleJun Xu0Shilong Xu1Mingyu Ma2Jing Ma3Chuanlong Li4School of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaSchool of Automation, Harbin University of Science and Technology, Harbin 150080, ChinaBlind and visually impaired (BVI) people face significant challenges in perception, navigation, and safety during travel. Existing infrastructure (e.g., blind lanes) and traditional aids (e.g., walking sticks, basic audio feedback) provide limited flexibility and interactivity for complex environments. To solve this problem, we propose a real-time travel assistance system based on deep learning. The hardware comprises an NVIDIA Jetson Nano controller, an Intel D435i depth camera for environmental sensing, and SG90 servo motors for feedback. To address embedded device computational constraints, we developed a lightweight object detection and segmentation algorithm. Key innovations include a multi-scale attention feature extraction backbone, a dual-stream fusion module incorporating the Mamba architecture, and adaptive context-aware detection/segmentation heads. This design ensures high computational efficiency and real-time performance. The system workflow is as follows: (1) the D435i captures real-time environmental data; (2) the processor analyzes this data, converting obstacle distances and path deviations into electrical signals; (3) servo motors deliver vibratory feedback for guidance and alerts. Preliminary tests confirm that the system can effectively detect obstacles and correct path deviations in real time, suggesting its potential to assist BVI users. However, as this is a work in progress, comprehensive field trials with BVI participants are required to fully validate its efficacy.https://www.mdpi.com/1424-8220/25/14/4518blind and visually impaireddeep learninglightweight designreal-time performancevibration feedback |
| spellingShingle | Jun Xu Shilong Xu Mingyu Ma Jing Ma Chuanlong Li Research and Implementation of Travel Aids for Blind and Visually Impaired People Sensors blind and visually impaired deep learning lightweight design real-time performance vibration feedback |
| title | Research and Implementation of Travel Aids for Blind and Visually Impaired People |
| title_full | Research and Implementation of Travel Aids for Blind and Visually Impaired People |
| title_fullStr | Research and Implementation of Travel Aids for Blind and Visually Impaired People |
| title_full_unstemmed | Research and Implementation of Travel Aids for Blind and Visually Impaired People |
| title_short | Research and Implementation of Travel Aids for Blind and Visually Impaired People |
| title_sort | research and implementation of travel aids for blind and visually impaired people |
| topic | blind and visually impaired deep learning lightweight design real-time performance vibration feedback |
| url | https://www.mdpi.com/1424-8220/25/14/4518 |
| work_keys_str_mv | AT junxu researchandimplementationoftravelaidsforblindandvisuallyimpairedpeople AT shilongxu researchandimplementationoftravelaidsforblindandvisuallyimpairedpeople AT mingyuma researchandimplementationoftravelaidsforblindandvisuallyimpairedpeople AT jingma researchandimplementationoftravelaidsforblindandvisuallyimpairedpeople AT chuanlongli researchandimplementationoftravelaidsforblindandvisuallyimpairedpeople |