Fitri Utaminingrum, M Ali Fauzi, Randy Cahya Wihandika, Sigit Adinugroho, Tri Astoto Kurniawan, Dahnial Syauqy, Yuita Arum Sari, Putra Pandu Adikara
People with physical disability such as quadriplegics may need a device which assist their mobility. Smart wheelchair is developed based on conventional wheelchair and is also generally equipped with sensors, cameras and computer based system as main processing unit to be able to perform specific algorithm for the intelligent capabilities. We develop smart wheelchair system that facilitates obstacle detection and human tracking based on computer vision. The experiment result of obstacle distance estimation using RANSAC showed lower average error, which is only 1.076 cm compared to linear regression which is 2.508 cm. The average accuracy of human guide detecting algorithm also showed acceptable result, which yield over 80% of accuracy. © 2017 IEEE.
Computer Vision Research Group, Faculty of Computer Science, Universitas Brawijaya, Malang, Indonesia
