Hierarchical control method for lower limb exoskeleton robot

Abstract

The present invention provides a layered control method for a lower limb exoskeleton robot. The specific implementation process is as follows: S1, analyzing the characteristic information of the sample, and constructing an outer layer control structure: setting the initial reference gait trajectory of the exoskeleton robot, and collecting The interaction torque between the exoskeleton robot and the sample; the initial reference gait trajectory is corrected, and the phase space reference gait trajectory is output; the initial reference gait trajectory is reset and the output of the outer control structure is periodically updated. S2. Based on the reference gait trajectory of S1, construct the inner layer control structure: collect the values ​​of the joint angle, speed and acceleration of the exoskeleton robot in real time; output the joint speed reference value of the exoskeleton robot based on the joint angle and the reference gait trajectory. S3. Based on the joint speed reference of S2, speed control is performed on the joint motors of the exoskeleton robot. The invention can adjust the output torque of the joint motor in real time according to the training situation, and improve the flexibility and training effect of the exoskeleton robot.

Description

technical field [0001] The invention relates to the field of exoskeleton robots, in particular to a layered control method for lower limb exoskeleton robots. Background technique [0002] With the development of robotics, especially exoskeleton robots have shown strong practicability and development potential in various fields including medical and military industries. [0003] However, traditional exoskeleton robots can only be limited to specific work content, and their motion trajectories are pre-planned before use. Although they can meet the requirements when dealing with fixed-scene tasks, they lack flexibility and users can only move passively. Or training, lack of active participation, once the task target changes or the exoskeleton user's own movement state changes, the predetermined task or training target will not be completed, and the compliance between the exoskeleton robot and the user is very poor, and even cause unnecessary damage in severe cases. Especially ...

AI Technical Summary

Problems solved by technology

[0003] However, traditional exoskeleton robots can only be limited to specific work content, and their trajectory is pre-planned before use. Although they can meet the requirements when dealing with fixed scene tasks, they lack flexibility and users can only move passively. Or training, lack of active participation, once the task goal changes or the exoskeleton user’s own motion state changes, it will not be able to complete the scheduled task or training goal, and the compliance performance between the exoskeleton robot and the user is very poor, and even unnecessary Especially for lower extremity exoskeleton users, once the user has a repulsive force with the exoskeleton robot, the exoskeleton robot will force the user to follow, which will easily cause the user to lose balance or even fall, and the training effect is not ideal

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