Extension and solution set dual neural network solution for robot motion planning

A robot motion and neural network technology, applied in the field of robot motion planning and control, to eliminate the problem of initial trial error and overcome the problem of error accumulation

Active Publication Date: 2018-05-11
SOUTH CHINA UNIV OF TECH
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AI Technical Summary

Problems solved by technology

In recent years, many recurrent neural networks have been applied to robot redundancy solving problems, b

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  • Extension and solution set dual neural network solution for robot motion planning
  • Extension and solution set dual neural network solution for robot motion planning
  • Extension and solution set dual neural network solution for robot motion planning

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Embodiment 1

[0051] A dual neural network solution to the motion planning of an extended solution set robot, comprising the following steps:

[0052] S1. Based on the given problem, obtain the current state of the robot through the sensor, and use the quadratic optimization scheme to analyze the inverse kinematics of the robot trajectory on the velocity layer. The designed performance index is the minimum velocity two-norm, which is constrained by each robot The joint angle limit and joint angular velocity limit of the joint and a nonlinear equation related to the motion of the robot;

[0053] S2, converting the quadratic optimization scheme of the robot minimum speed two-norm index designed in step S1 into a standard quadratic programming problem;

[0054] S3, converting the quadratic programming problem of the robot into the solution of the Karush-Kuhn-Tucker optimization condition in step S2;

[0055] S4, using a dual neural network solver to expand the solution set to solve the Karush...

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Abstract

The invention discloses an extension and solution set dual neural network solution for robot motion planning. The extension and solution set dual neural network solution for robot motion planning comprises the steps of acquiring a current state of a robot through a sensor, and adopting a quadratic optimization scheme for carrying out inverse kinematics analysis on a robot track on a speed layer; converting a quadratic optimization scheme of a minimum speed two-norm index to a standard quadratic planning problem; converting the quadratic planning problem to a solution of a Karush-Kuhn-Tucker optimality condition; utilizing an extension and solution set dual neural network solver for solving; and transferring a solved result to a robot controller, and driving a robot body to carry out trajectory tracking. According to the extension and solution set dual neural network solution for robot motion planning provided by the invention, through designing nonlinear equality constraint, convex setconstraint and non-convex set constraint can be compatible, a preliminary test error problem occurred in robot control is eliminated, and an error accumulation problem during a robot control processis solved.

Description

technical field [0001] The invention relates to the technical field of robot motion planning and control, in particular to an extended solution set dual neural network solution for robot motion planning. Background technique [0002] In recent years, robotic arms have been used in various fields, such as medical rehabilitation, aviation manufacturing, and household services. More and more researchers are also investing in the research of controlling robot arms and tracking various complex trajectories. [0003] A redundant robot is one that has more degrees of freedom than the minimum required to complete a task. This allows for greater flexibility and fault tolerance in redundant robots. The additional degrees of freedom can be designed to optimize some secondary sub-tasks while accomplishing the intended task of the end effector. [0004] How to obtain the inverse kinematic solution accurately and in real time is a challenging problem in redundant robot motion planning....

Claims

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/161
Inventor 张智军陈思远
Owner SOUTH CHINA UNIV OF TECH
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