Path Planning And Control Of Upper Limb Rehabilitation Rraining Robot

In recent years,due to the increasing number of patients with upper limb limb motor dysfunction due to accidents,diseases and other factors,the demand for upper limb rehabilitation treatment has also gradually increased.Based on the development of modern robotics and the medical industry,the research on rehabilitation training robots has gradually become a hot topic in the industry,which is of great significance to the development of the national medical rehabilitation industry.Therefore,in this paper,a four-degree-of-freedom upper limb rehabilitation training robot is taken as the research object,and its path planning and control algorithms are studied to assist the rehabilitation training of patients with upper limb dysfunction.In this paper,based on the fundamental theory of robotics,we first model the fourdegree of freedom upper limb rehabilitation robot,use the D-H method to build the rehabilitation robot model,derive the kinematic positive inverse solution,calculate theJacobian matrix of the robot,and then obtain its workspace by Monte Carlo method,and simulate the built rehabilitation robot using Matlab.Then the total kinetic energy and total potential energy of the rehabilitation robot are calculated separately,and the kinetic model is built using the Lagrange method,use Solidworks to build a robot model for upper limb rehabilitation,and import it into Adams for simulation analysis to get information on the angular velocity,angular acceleration,joint moment,etc.of each joint during robot movement.Secondly,the control strategy of the rehabilitation robot is studied.Sliding mode and active disturbance rejection combined control methods based on the extended state observer are proposed.The advantages of sliding mode control and active disturbance rejection control are used respectively,Sliding mode control is used for fast approach,and auto-disturbance is used to avoid chattering on the sliding mode surface.Matlab was used to simulate sliding mode control,active disturbance rejection control and sliding mode adaptive disturbance rejection control based on extended state observer.Experimental results show that the proposed control algorithm has higher trajectory tracking accuracy and faster tracking.Speed,has good anti-interference ability to external interference,and at the same time has good robustness to the internal non-linear disturbance of the system.Finally,common methods of trajectory planning and path planning are analyzed,and trajectory planning methods for third and fifth polynomial interpolation and spatial linear,spatial arc interpolation are analyzed.For path planning,in order to make rehabilitation more relevant to the actual condition of the affected limb while avoiding too homogeneous a path of activity,a path planning algorithm combining a randomly extended tree with an artificial potential field was proposed and validated using Matlab simulation.The experimental results show that the optimization algorithm using the randomized extended tree to improve the artificial potential field effectively avoids the local optimization problem,has a good path planning ability,can target patients with limb damage,avoid the area that will cause injury,plan a reasonable training path,flexibly adapt to patients with various degrees of damage,while avoiding the training path single problem.