Mechanical arm motion time optimization method based on joint performance limitation

Abstract

The invention belongs to the technical field of mechanical arm control, and particularly discloses a mechanical arm motion time optimization method based on joint performance limitation. The mechanical arm motion time optimization method comprises the following steps of (1) constructing mapping; (2) carrying out torque limitation on a mechanical arm joint motor; (3) carrying out acceleration solving on track point positions to obtain acceleration limit values; (4) mapping the speed limit of the mechanical arm joint motor into the speed limit of an end effector moving along a track, and obtaining a corresponding () plane curve based on the speed limit of the joint motor; (5) carrying out front and back numerical integration processing on the acceleration limit values of the various characteristic track point positions, and obtaining a corresponding () plane curve based on joint motor torque limitation; (6) combining the curves to obtain a track length-speed limit curve; and (7) completing mechanical arm motion time optimization. By means of the mechanical arm motion time optimization method, the algorithm is simple, the mechanical arm motion speed is effectively increased based on the performance of the mechanical arm joint motor, and the motion time optimization is achieved.

Description

technical field [0001] The invention relates to the technical field of manipulator control, in particular to a method for optimizing the movement time of a manipulator based on joint performance limitations. Background technique [0002] The application of robotic arms has greatly improved production efficiency. With the implementation of intelligent manufacturing policies, the application range of robots has become more and more extensive. When designing a mechanical arm, the performance of the joint motor often depends on the engineer's work experience, and the fixed motion trajectory is simulated to determine the selection of the joint motor. For the user of the manipulator, the planned motion trajectory is complex and changeable. When the manipulator runs along the trajectory set by the user, its end effector often moves along the trajectory at a lower speed. Although this guarantees The robotic arm can complete the planned trajectory, but it does not give full play to ...

AI Technical Summary

Problems solved by technology

For the user of the manipulator, the planned motion trajectory is complex and changeable. When the manipulator runs along the trajectory set by the user, its end effector often moves along the trajectory at a lower speed. Although this guarantees The robotic arm can complete the planned trajectory, but it does not exert the maximum efficiency of the performance of the joint motor

In the existing technology, in order to increase the speed of the movement trajectory of the robotic arm and optimize the movement time, most of them use intelligent algorithms such as neural networks, but this requires a large amount of data sets for training, which not only consumes time but also requires engineering experience to adjust parameters

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