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A motion planning method of primal-dual neural network robot with nonlinear constraints

A technology of nonlinear constraints and neural network, applied in the field of robot motion planning with primal dual neural network, to achieve the effect of overcoming the problem of error accumulation and eliminating the problem of initial error

Active Publication Date: 2020-05-22
SOUTH CHINA UNIV OF TECH
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

Many recurrent neural networks have been applied to robot redundancy solving problems, but these neural network methods are mainly for robot motion planning problems with convex set constraints

Method used

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  • A motion planning method of primal-dual neural network robot with nonlinear constraints
  • A motion planning method of primal-dual neural network robot with nonlinear constraints
  • A motion planning method of primal-dual neural network robot with nonlinear constraints

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Embodiment 1

[0048] A primal-dual neural network robot action planning method under nonlinear equality constraints, including the following steps:

[0049] S1. Based on the desired task, the current state of the robot is acquired through sensors and the quadratic optimization scheme is used to analyze the robot trajectory in the speed layer. The performance index of the quadratic optimization scheme is the minimum speed two norm and has A feasible set constraint of a nonlinear equality constraint and a robot joint angle;

[0050] S2. Transform the quadratic optimization scheme of the robot based on nonlinear constraints designed in step S1 into a standard form of a quadratic programming problem;

[0051] S3. Solving a standard quadratic programming optimal solution problem in step S2 is equivalent to solving a linear variational inequality problem;

[0052] S4. Convert the linear variational inequality problem in step S3 into a solution to a piecewise linear projection equation based on nonlinear ...

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Abstract

The invention discloses a nonlinear constrained primal-dual neural network robot action planning method, which comprises the steps of acquiring a current state of a robot, and adopting a quadratic optimization scheme for carrying out inverse kinematics analysis on a robot track on a speed layer; converting the quadratic optimization scheme to a standard form of a quadratic planning problem; enabling a quadratic planning optimization problem to be equivalent to a linear variational inequality problem; converting the linear variational inequality problem to a solution of a piecewise linearity projection equation based on nonlinear equality constraint; utilizing a nonlinear constrained primal-dual neural network solver for solving the piecewise linearity projection equation; and transferringa solved instruction to a robot instruction input port, and driving a robot to carry out path follow. According to the nonlinear constrained primal-dual neural network robot action planning method provided by the invention, convex set constraint 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 process is solved.

Description

Technical field [0001] The invention relates to the technical field of robot motion planning and control, in particular to a non-linearly constrained proto-dual neural network robot motion planning method. Background technique [0002] In recent years, industrial robots and robotic arms have attracted more and more attention. In industrial manufacturing, medical rehabilitation, entertainment, military research, and space exploration, robots have unique meanings. In order to give robots more flexible functions, the research of robot motion planning and control methods in practical applications plays a unique role. [0003] Robots are usually divided into non-redundant robots and redundant robots. Redundant robots are robots that have more degrees of freedom than the minimum required to complete the task. With more degrees of freedom, redundant robots can complete additional secondary tasks. This also makes redundant robots have greater flexibility and fault tolerance than non-re...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): B25J9/16
CPCB25J9/16B25J9/1664
Inventor 张智军陈思远
Owner SOUTH CHINA UNIV OF TECH
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