TY - JOUR N2 - Rat robots have great potential in rescue and search tasks because of their excellent motion ability. However, most of the current rat-robot systems relay on human guidance due to variable voluntary motor behaviour of rats, which limits their application. In this study, we developed a real-time system to detect a rat robot’s transient motion states, as the prerequisite for further study of automatic navigation. We built the detection model by using a wearable inertial sensor to capture acceleration and angular velocity data during the control of a rat robot. Various machine learning algorithms, including Decision Trees, Random Forests, Logistic Regression, and SupportVector Machines,were employed to performthe classification of motion states. This detection system was tested in manual navigation experiments, with detection accuracy achieving 96.70%. The sequence of transient motion states could be further used as a promising reference for offline behaviour analysis. L1 - http://journals.pan.pl/Content/120096/art02.pdf L2 - http://journals.pan.pl/Content/120096 PY - 2021 IS - No 2 EP - 268 DO - 10.24425/mms.2021.136605 KW - inertial sensor KW - real-time measurement KW - rat robot KW - motion state A1 - Chen, Yuxin A1 - Xu, Haoze A1 - Yang, Wei A1 - Yang, Canjun A1 - Xu, Kedi PB - Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation VL - vol. 28 DA - 2021.07.01 T1 - Rat robot motion state identification based on a wearable inertial sensor SP - 255 UR - http://journals.pan.pl/dlibra/publication/edition/120096 T2 - Metrology and Measurement Systems ER -