Optimal Control Of NAO Robot Arm Motion

Service robots are developing rapidly and intelligently,especially in treating autistic children,supporting the elderly to carry out sports activities,monitoring their physical signs,and interacting with human beings.In these applications,A-star algorithm and adaptive control strategy is used to study the randomness of path node selection in the path planning of NAO robot,and the lack of systematic control algorithm of the arm in this paper.Firstly,in order to make NAO use arm flexibly and reach the target position,the target object can be recognized by Naomarks,and the orientation information of the object can be obtained quickly and accurately.According to the inverse kinematics solution,the workspace of the robot arm is solved,and the trajectory planning of the robot arm is carried out.Because the object position is fixed from the beginning to the end and the whole environment is static network,the workspace is searched by a fast and direct heuristic function,and the optimal node is selected according to the search information given by the object.Then the joint space is transformed from Cartesian space to joint space,and the joint variables are obtained,and the trajectory planning is carried out.Secondly,aiming at the accurate control problem of NAO arm grasping object trajectory,the motion model of NAO arm is established and the appropriate control strategy is selected.After analyzing the structure of the left arm of NAO,the Denavit-Hartenberg theory is used to determine the coordinate data of the arm,the D-H kinematics parameters are obtained,the kinematics equation of the arm is solved,and the inverse kinematics formula of the arm is calculated by geometric method.In order to control the robot arm more efficiently,the dynamic model of the arm is established,and the PD controller and the adaptive controller are designed according to the model.According to the results of Simulink,the adaptive controller has good tracking and robustness to the robot arm motion when the system has a large disturbance.