Rehabilitation robot control method and device and rehabilitation robot
A rehabilitation robot and control method technology, which is applied in the direction of program-controlled manipulators, neural learning methods, manipulators, etc., can solve the problems of low prediction value accuracy and poor versatility of neural network models, so as to improve versatility and accuracy Effect
Pending Publication Date: 2022-02-11
SHENZHEN WISEMEN MEDICAL TECH CO LTD
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[0002] When current rehabilitation robots perform rehabilitation training, they usually set a certain target position and assist the part to be trained to reach the set target position. With the development of deep learning technology, more and more rehabilitation robots use deep learning to solve the problem of rehabilitation robots. The training control problem of the commonly used rehabilitation robots is to conduct offline training of the neural network model based on historical data, and then perform training control based on the neural network model obtained from the offline training, but the neural network model obtained from the offline training is general The usability is poor, and the accuracy of the predicted value obtained is low
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[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be described below in conjunction with the accompanying drawings. Apparently, the described embodiments are some of the embodiments of the present invention, but not all of them.
[0029] There are two well-known problems in robot dynamics control, the direct problem and the inverse problem. The forward problem is to know the driving force of the motor at each joint of the robot, and predict the final position, momentum and acceleration of the robot arm; the inverse problem is to move the robot arm to the specified position and have the specified momentum or acceleration. How the motor driving force needs to be distributed. At present, the commonly used treatment plan for upper limb rehabilitation robots is to set a certain target position and require the patient's limbs to reach the target position w...
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The invention provides a rehabilitation robot control method and device and a rehabilitation robot, and relates to the technical field of robot control; wherein the rehabilitation robot control method comprises the steps: S102, inputting a training target into a trained neural network model for moment prediction, and obtaining a moment prediction value of a to-be-trained joint; s104, controlling the to-be-trained joint to move according to the training target based on the moment predicted value; s106, acquiring and storing actual motion data generated by the to-be-trained joint, and updating the training data set based on the actual motion data; s108, performing update training on the neural network model based on the updated training data set, and returning the updated and trained neural network model as a new trained neural network model to the step S102. According to the invention, universality of the neural network model can be improved, and the accuracy of the predicted value of the neural network model is improved.
Description
technical field [0001] The present invention relates to the technical field of robot control, in particular to a rehabilitation robot control method, device and rehabilitation robot. Background technique [0002] When current rehabilitation robots perform rehabilitation training, they usually set a certain target position and assist the part to be trained to reach the set target position. With the development of deep learning technology, more and more rehabilitation robots use deep learning to solve the problem of rehabilitation robots. The training control problem of the commonly used rehabilitation robots is to conduct offline training of the neural network model based on historical data, and then perform training control based on the neural network model obtained from the offline training, but the neural network model obtained from the offline training is general The applicability is poor, and the accuracy of the predicted value obtained is low. Contents of the inventio...
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IPC IPC(8): A61H1/02B25J9/16G06N3/04G06N3/08
CPCA61H1/0274A61H1/0237B25J9/16G06N3/084A61H2201/1207A61H2201/1659A61H2201/5007A61H2205/06A61H2205/10G06N3/045
Inventor 孙维黄冠
Owner SHENZHEN WISEMEN MEDICAL TECH CO LTD