COVID-19 Pandemic Response Robot

Due to an arising COVID-19 positive confirmed case in Taiwan, the screening of body temperature, mask wearing and quarantined violation is enhanced. A mobile robot that conducts this task demanded reduce human labor. However, conventional robots suffer from several limitations, perceptual aliasing (e.g., different places/objects can appear identical), occlusion place/object appearance changes between visits), viewpoints, scale objects, low mobility, less functionality, some environmental limitations. As for thermal imager, it displays current heat spectrum colors, needs manual monitoring. This paper proposes applying Simultaneous Localization Mapping unknown environment using deep learning detection wearing, face on Raspberry Pi overcome these problems. It also uses A* algorithm do path planning obstacle avoidance via 3D Light Detection Ranging make move more smoothly. Evaluating implementing algorithms models, then selecting most suitable method. Root Mean Square Error three are compared. The predictions models evaluated metrics (model speed, accuracy, complexity, precision, recall, precision–recall curve, F1 score). In conclusion, Google Cartographer building a map, Convolutional Neural Network detection, only looking once achieve best result among all algorithms.