Thermal comfort measurement using thermal-depth images for robotic monitoring

•An application of thermal depth images from a mobile robot to human thermal comfort measurement is proposed.•The proposed method is based on an established thermal comfort measure in the architecture domain.•Thermal comfort measurement is performed more conveniently than existing methods by using thermal-depth images.•Quantitative evaluations have been conducted for clothing insulation and PMV measurement. This paper describes an application of thermal-depth images to human thermal comfort measurement. A mobile monitoring of the elderly and residents of care houses is one of the promising applications of mobile assistive robots. Monitoring if a person feels comfortable is an important task of such robots. We rely on an established comfort measure in the architecture domain, namely, predicted mean vote (PMV). PMV is calculated mainly by six factors and one of which is the clothing insulation or clo-value. Clo-values are usually measured by a thermal mannequin, a specially-designed apparatus for the purpose. We apply human recognition techniques in thermal-depth images to efficiently measure clo-values, thereby enabling on-line assessment of thermal comfort. We evaluate the method and develop a mobile robot system for experimental testing.