Sistem Guided Following Control pada Smart Wheelchair menggunakan Metode Yolov5 berbasis Nvidia Jetson TX2 - Alfianto Palebangan; Fitri Utaminingrum (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2022)
Smart wheelchairs are becoming increasingly popular for individuals with mobility impairments, allowing them to navigate their environment with more independence and comfort. However, one challenge faced by smart wheelchairs is the ability to follow a designated guide, such as a human or guide rope. In this abstract, the researcher proposes the use of the YOLOv5 (You Only Look Once version 5) method to enable smart wheelchairs to follow a guide. YOLOv5 is a fast and accurate object detection algorithm, making it suitable for real-time applications such as guiding a smart wheelchair. By using YOLOv5 to detect and track a designated guide, the smart wheelchair can smoothly and responsively follow the guide, allowing the user to easily navigate their environment. To demonstrate the effectiveness of the research approach, the researcher conducted a series of experiments on a smart wheelchair equipped with a camera and a YOLOv5-based guide following system. The research results showed that the smart wheelchair was able to accurately follow the designated guide. This study demonstrates the potential of YOLOv5 for guiding a smart wheelchair and the researcher believes that this approach has the potential to enhance mobility for wheelchair users in their daily activities.