Design method for Variable parameter neural solver for motion planning of redundancy mechanical arm
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A motion planning and design method technology, applied in the direction of manipulators, program control manipulators, instruments, etc., can solve unreasonable and unsatisfactory problems
Active Publication Date: 2018-05-04
SOUTH CHINA UNIV OF TECH
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When the neural network is applied in the actual system, such a requirement is often difficult to meet
In addition, in the actual system, the reciprocal of the inductance parameter value and the capacitance pa
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[0072] Example 1
[0073] figure 1 Shown is a flow chart of a variable-parameter neural solver design method of an example of the present invention; a variable-parameter neural solver design method for redundant robotic arm motion planning, comprising the following steps:
[0074] 1) Formalize the task to be solved into the performance index and constraint conditions of the redundant manipulator, that is, model the actual redundant manipulator parameter index, and establish a physical system model;
[0075] 2) Convert the physical system model in step 1) into the time-varying quadratic programming standard form of the system;
[0076] 3) According to the Lagrange multiplier method, the quadratic programming model in step 2) is optimized for the optimal value;
[0077] 4) converting the optimization information in step 3) into a standard time-varying matrix form;
[0078] 5) Design deviation function equation based on the matrix in step 4);
[0079] 6) Based on the deviatio...
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[0127] Example 2
[0128] In order to demonstrate the actual system design process, an example of a 6-DOF robotic arm is used to illustrate the problem: the MATLAB simulation experiment of this example is based on Kinova-JACO 2 Based on the lightweight bionic robotic arm. The total weight of this type of robotic arm is 4.4kg, and the maximum control distance is 77cm.
[0129] This type of redundant manipulator contains a total of 6 degrees of freedom, that is, θ(t) contains 6 elements; the spatial dimension of the end of the manipulator is 3, including the three directions of X axis, Y axis and Z axis; Its Jacobian matrix is The starting joint angle of the redundant manipulator is set as θ(0)=[1.675,2.843,-3.216,4.187,-1.710,-2.650]; the task execution period t is set as 8s; the parameter γ is set as Set at 50. In this example, in order to demonstrate the superiority of the variadic neural solver for redundant manipulator motion planning proposed by the present invention,...
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Abstract
The invention discloses a design method for a variable parameter neural solver for motion planning of a redundancy mechanical arm. The method comprises the following steps that the solved task is converted into a performance index and a constraint condition of the redundancy mechanical arm; the performance index and the constraint condition is converted into a time-varying quadratic programming standard form of a to-be-solved system; according to a lagrangian multiplier method, the optimal value in the time-varying quadratic programming standard form is optimized; optimized information is converted into a standard time-varying matrix equation form; a deviation function is designed according to the standard time-varying matrix equation form; according to the deviation function and a power type variable parameter recursion neural dynamics method, the variable parameter neural solver used for the motion planning of the redundancy mechanical arm on a real number field is designed; and a network state solution obtained through the variable parameter neural solver is the optimal solution for the motion planning of the redundancy mechanical arm system. The method has the advantages of being high in calculation speed, high in precision, fast in convergence, high in instantaneity, and good in robustness.
Description
technical field [0001] The patent of the invention belongs to the robot motion planning method, in particular to a design method of a variable parameter neural solver for redundant mechanical arm motion planning. Background technique [0002] Redundant manipulator refers to the degree of freedom (Degrees of Freedom, or DOF) of the manipulator is greater than the degree of freedom necessary to complete the task. With more degrees of freedom, the redundant manipulator can also complete additional tasks such as obstacle avoidance, joint angle limit constraints, and the singular state of the manipulator while completing various tasks of the end effector. The traditional method for solving the inverse kinematics problem of redundant manipulators is based on the pseudo-inverse method. This method has a large amount of calculation and cannot solve the inequality problem, which is greatly restricted in the actual application and operation of the manipulator. In recent years, a sol...
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