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The rapid growth of the elderly population has led to an increased demand for effective and personalized eldercare solutions. In this paper, the design and development of an eldercare robot is presented. This robot is specifically tailored to meet the two specific challenges faced by the elderly. The first is the continuous indoor tracking of the elder, while the second is the fall detection. A comprehensive overview of the hardware and software components, as well as the control architecture of the robot is presented. The hardware design of the robot incorporates a range of features, including a perception system comprising a 2D Lidar, IMU, and camera for environment mapping, localization, and fall detection. The software stack of the robot is explained as consisting of layers for perception, mapping, and localization. The robot is tested experimentally to validate its path planning capability by using Hector SLAM and the RRT* technique. Experimental path planning has shown a positioning accuracy of 93.8% on average. Elderly fall detection is achieved by using the YOLOv7 algorithm at a percentage of 96%. Experimental results have been discussed and evaluated.
Elwaly et al. (Tue,) studied this question.
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