The working performance of teleoperation largely depends on the operators operation skills,operation status and other factors.In order to suppress the slave hand jitter and the increase of master-slave trajectory tracking error caused by operator misoperation,physiological tremor and other non-uniform traction movements,a teleoperation control strategy supporting lowpass filter and artificial neural network was proposed.According to the frequency band distribution of human body jitter signal,a lowpass filter was used to filter the jitter signal generated by the operators physiological tremor.According to the mapping relationship between the variation characteristics of operation signal and the proportion of master-slave motion gain during non-uniform motion,artificial neural network was used to realize variable gain control to reduce the master-slave trajectory tracking error.Finally,experiments show that the teleoperation scheme supporting lowpass filtering and artificial neural network improves the working quality of teleoperation robot on the whole.