Omobot: 自律探索と転倒検知を行う低コスト移動ロボット
Omobot: a low-cost mobile robot for autonomous search and fall detection
低コストな全方向移動ロボットで高齢者を探索し、転倒を検知すると指定された連絡先にメールを送るシステムを開発。カメラ視点を人間視点に変換するホモグラフィで転倒検知精度を向上させた。
著者: Shihab Uddin Ahamad, Masoud Ataei, Vijay Devabhaktuni, Vikas Dhiman
分類: cs.RO
原文アブストラクト
Detecting falls among the elderly and alerting their community responders can save countless lives. We design and develop a low-cost mobile robot that periodically searches the house for the person being monitored and sends an email to a set of designated responders if a fall is detected. In this project, we make three novel design decisions and contributions. First, our custom-designed low-cost robot has advanced features like omnidirectional wheels, the ability to run deep learning models, and autonomous wireless charging. Second, we improve the accuracy of fall detection for the YOLOv8-Pose-nano object detection network by 6% and YOLOv8-Pose-large by 12%. We do so by transforming the images captured from the robot viewpoint (camera height 0.15m from the ground) to a typical human viewpoint (1.5m above the ground) using a principally computed Homography matrix. This improves network accuracy because the training dataset MS-COCO on which YOLOv8-Pose is trained is captured from a human-height viewpoint. Lastly, we improve the robot controller by learning a model that predicts the robot velocity from the input signal to the motor controller.
