Driving Assistance System with Obstacle Avoidance for Electric Wheelchairs
- Authors
- Erturk, Esranur; Kim, Soonkyum; Lee, Dongyoung
- Issue Date
- 2024-07
- Publisher
- Multidisciplinary Digital Publishing Institute (MDPI)
- Citation
- Sensors, v.24, no.14
- Abstract
- A system has been developed to convert manual wheelchairs into electric wheelchairs, providing assistance to users through the implemented algorithm, which ensures safe driving and obstacle avoidance. While manual wheelchairs are typically controlled indoors based on user preferences, they do not guarantee safe driving in areas outside the user's field of vision. The proposed model utilizes the dynamic window approach specifically designed for wheelchair use, allowing for obstacle avoidance. This method evaluates potential movements within a defined velocity space to calculate the optimal path, providing seamless and safe driving assistance in real time. This innovative approach enhances user assistance and safety by integrating state-of-the-art algorithms developed using the dynamic window approach alongside advanced sensor technology. With the assistance of LiDAR sensors, the system perceives the wheelchair's surroundings, generating real-time speed values within the algorithm framework to ensure secure driving. The model's ability to adapt to indoor environments and its robust performance in real-world scenarios underscore its potential for widespread application. This study has undergone various tests, conclusively proving that the system aids users in avoidance obstacles and ensures safe driving. These tests demonstrate significant improvements in maneuverability and user safety, highlighting a noteworthy advancement in assistive technology for individuals with limited mobility.
- Keywords
- DESIGN; smart electric wheelchair; LiDAR sensor; dynamic window approach; obstacle avoidance; driving assistant system
- ISSN
- 1424-8220
- URI
- https://pubs.kist.re.kr/handle/201004/150378
- DOI
- 10.3390/s24144644
- Appears in Collections:
- KIST Article > 2024
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