The invention provides a human-
machine cooperation
assembly planning method based on
human body real-time
muscle fatigue, and relates to the technical field of human-
machine cooperation
assembly manufacturing, and the method comprises the steps: constructing a
muscle fatigue index model through a multi-angle motion image set, a
human body skeletal muscle model and a biomechanical
data set; training the
deep learning model through the sample
assembly action image set, and constructing an action
category recognition model; according to the actual assembly action image set, the human
skeletal muscle model, the
muscle fatigue index model and the action
category recognition model, the actual assembly time consumption and the actual fatigue accumulated value of the person are obtained through calculation; and based on the actual assembly time consumption of the
robot, the actual assembly time consumption of the person and the actual fatigue accumulated value, an optimal
population is obtained through calculation of a multi-target
genetic algorithm, and an optimized man-
machine cooperation assembly process is obtained through the optimal
population. According to the method,
human muscle fatigue and assembling action time consumption are monitored in a non-invasive and real-time mode, the man-machine cooperation assembling procedure is dynamically adjusted, the man-machine cooperation assembling efficiency is improved,
human muscle fatigue is reduced, and meanwhile the method is more suitable for the actual assembling environment.