主催: 一般社団法人 日本機械学会
会議名: ロボティクス・メカトロニクス 講演会2018
開催日: 2018/06/02 - 2018/06/05
We propose an advanced system that infers and visualizes the behavior of search and rescue (SAR) dogs while they are searching for victims in disaster sites where human cannot enter. Our system robustly infers SAR dogs’ behavior using machine learning methods with inertial data obtained from sensors attached to them. It automatically estimates the probability of each of the behavior candidates “running”, “walking”, “stopping”, “barking”, “sniffing some objects”, and “sniffing the air,” and presents the most likely one in real time. We also developed a system that visualizes the results of inference for handlers and rescue supervisors’ convenience.