Redundant robot repetitive motion planning method adopting parabolic final state neural network

A neural network, repetitive motion technology, applied in manipulators, program-controlled manipulators, manufacturing tools, etc., can solve problems such as difficult implementation, low calculation accuracy, and inability to converge in a limited time.

Active Publication Date: 2019-01-08
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0025] In order to overcome the shortcomings of the existing redundant robot repetitive motion planning method that cannot converge in a limited time, the calculation accuracy is low, and it is not easy to implement, the present invention provides a parabolic final state that has a limited time convergence, high calculation accuracy, and is easy to implement. Redundant robot motion planning method based on neural network

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  • Redundant robot repetitive motion planning method adopting parabolic final state neural network
  • Redundant robot repetitive motion planning method adopting parabolic final state neural network
  • Redundant robot repetitive motion planning method adopting parabolic final state neural network

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Embodiment Construction

[0099] The present invention will be further described below in conjunction with the accompanying drawings.

[0100] refer to Figure 1 to Figure 9 , a repetitive motion planning method for redundant robots using a parabolic final-state neural network, figure 1 It is a flow chart of the redundant robot repetitive motion planning scheme, which consists of the following three steps: 1. Determine the expected trajectory of the redundant robot end effector and the expected angles of each joint; 2. Adopt the asymptotic convergence performance index and form the redundant The quadratic planning scheme for repetitive motion of the robot; 3. Solve the quadratic programming problem with a parabolic final state neural network to obtain the angular trajectory of each joint, including the following steps:

[0101] 1) Determine the desired trajectory

[0102] Set the desired reunification of the redundant robot PA10 Determine the coordinates of the center of the circle trajectory (x=0....

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Abstract

The invention discloses a redundant robot repetitive motion planning method adopting a parabolic final state neural network. The redundant robot repetitive motion planning method adopting the parabolic final state neural network comprises the following steps: giving an expected trajectory rd(t) of a robot end-actuator in cartesian space, and giving expected folding angles theta d (0) of each joint; and taking the parabolic final state neural network as a solver for repetitive motion of a robot by converting a quadratic optimizing problem about redundant robot trajectory planning into a time-varying matrix equation solving problem by adopting an asymptotically convergent performance index. In the situation of initial position offset, a repetitive motion planning task with finite time convergence of the redundant robot is realized. The invention provides the redundant robot repetitive motion planning method adopting the parabolic final state neural network, which has the finite time convergence, high computing accuracy and easiness in implementation.

Description

technical field [0001] The invention relates to a repetitive motion planning technology for industrial robots. Specifically, it proposes a redundant robot repetitive motion planning method using a parabolic final state neural network that converges in a limited time and the initial position deviates from the expected trajectory. Background technique [0002] Redundant robots have good flexibility and fault tolerance. It can use the extra degrees of freedom to enhance obstacle avoidance without affecting the operation of the end effector, and can complete variable tasks in complex working environments. At present, redundant robots have played an important role in many application fields, such as manufacturing, medical equipment, logistics and transportation, military defense, etc. [0003] The number of joints n of the redundant robot is greater than the degree of freedom m required by the end effector to perform the expected task, which makes the redundant robot have greater...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16
CPCB25J9/1664
Inventor 孙明轩张钰吴雨芯
Owner ZHEJIANG UNIV OF TECH
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