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About

Kaichiro Nishi is a robotics researcher whose work sits at the intersection of human-aware automation, thermal sensing, and assistive technology. His primary research areas include thermal comfort monitoring, human pose estimation, and motion planning for service and care robots. Nishi’s most influential contribution is his pioneering use of thermal-depth imaging for robotic monitoring. His 2019 paper, "Thermal comfort measurement using thermal-depth images for robotic monitoring," has garnered 45 citations, establishing a foundation for non-contact assessment of human thermal states in indoor environments. In related work, he developed methods to combine 3D point cloud data with thermal information, enabling robots to simultaneously recognize human posture and evaluate environmental conditions—a dual capability critical for lifestyle support robots. Nishi has also addressed practical challenges in elder care robotics, notably with a head position estimation method for recumbent individuals, designed to help care robots detect and assist fallen persons using laser range finders and point cloud matching. More recently, he has explored deep reinforcement learning for evolvable motion planning, aiming to create robots that can adapt to dynamic factory and warehouse environments. Through his integration of thermal sensing with spatial intelligence, Nishi is advancing the next generation of context-aware, human-centric robots.