{"title":"A sensor platform for the visually impaired to walk straight avoiding obstacles","authors":"S. Silva, D. Dias","doi":"10.1109/ICSENST.2015.7438513","DOIUrl":null,"url":null,"abstract":"We present a sensor platform to be mounted on the white cane used by the visually impaired. This can estimate the direction of user movement and enable the user to detect obstacles lying on the path in advance. The sensor platform contains an ultrasonic sensor and an IMU (Inertia Measurement Unit). We develop a model to estimate distances to obstacles in the path and their width based on sensor measurements. The model is demonstrated to have an overall accuracy of 84%, with accuracy as high as 90% for obstacles within 50cm in front of the user. Knowledge of obstacle locations and their size in advance, would enable us to guide visually impaired persons to deviate from their path and return to it after the obstacle has been passed.","PeriodicalId":375376,"journal":{"name":"2015 9th International Conference on Sensing Technology (ICST)","volume":"463 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 9th International Conference on Sensing Technology (ICST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSENST.2015.7438513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
We present a sensor platform to be mounted on the white cane used by the visually impaired. This can estimate the direction of user movement and enable the user to detect obstacles lying on the path in advance. The sensor platform contains an ultrasonic sensor and an IMU (Inertia Measurement Unit). We develop a model to estimate distances to obstacles in the path and their width based on sensor measurements. The model is demonstrated to have an overall accuracy of 84%, with accuracy as high as 90% for obstacles within 50cm in front of the user. Knowledge of obstacle locations and their size in advance, would enable us to guide visually impaired persons to deviate from their path and return to it after the obstacle has been passed.