Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Robot simulation learning method based on dynamic system model

A dynamic system model, a technology for robotics, applied in the field of artificial intelligence and robot control

Inactive Publication Date: 2019-05-03
BEIJING UNIV OF TECH
View PDF2 Cites 28 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Aiming at the problems existing in the existing robot imitation learning methods, the present invention proposes a robot imitation learning method based on a dynamic system model

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Robot simulation learning method based on dynamic system model
  • Robot simulation learning method based on dynamic system model
  • Robot simulation learning method based on dynamic system model

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach

[0064] A method of imitation learning for robots based on dynamic system models is used for robots to learn motor skills from human teaching. Through the way of teaching by hand, drag the end of the robotic arm to perform motion teaching, complete a motion task similar to picking and placing objects, and record the data of the teaching motion trajectory. Through the learning of the learning algorithm, the purpose of reproducing the teaching movement is achieved. The specific implementation is as follows:

[0065] Step 1. Complete the required teaching movement by teaching by hand. The internal joint sensor of the mechanical arm records the change of each joint angle during the movement. By connecting the upper computer program of the mechanical arm, the positive movement of the mechanical arm Learn to solve the change of the position and velocity of the end effector, and record it as for subsequent motion modeling. As shown in Figure 2(a), it is a single simple teaching mo...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a robot simulation learning method based on a dynamic system model. Simulation of teaching movement of the robot is achieved through learning, specifically, the demonstration motion is modeled into a nonlinear dynamic system model through a gaussian mixture model, in addition, the stability of the motion model is guaranteed through the method with the additional stability constraint conditions, the parameter learning problem of the motion model is converted into a constraint optimization problem, so that a complete description of the motion model is obtained, and finally, the motion model obtained through learning is used as a control strategy to guide the robot to imitate the teaching motion. The method is used for teaching motion of target point fixation, the method has good stability, all the generated motion trails are converged to a target point, and has good expression capacity for simple and complex teaching movement, the generalization ability of the motion model is good, a motion track which is smooth and can be converged to a target can be generated outside the teaching movement range.

Description

technical field [0001] The invention belongs to the field of artificial intelligence and robot control, in particular to a method for robot imitation learning based on a dynamic system model. Background technique [0002] At present, in the research of robotics, how to make robots have intelligent behaviors similar to humans has become a major research hotspot. The imitation learning developed from human learning, as one of the ways for robots to directly acquire knowledge and skills, has played an increasingly important role in improving the intelligence of robots, and has been increasingly recognized by the academic community. Follow and research. The main reason is that, on the one hand, compared with traditional robot programming control, imitation learning will make robot programming easier, reduce the professional requirements for operators, and greatly improve the working efficiency of robots; on the other hand, imitation learning endows The ability of robots to acq...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): B25J9/16
Inventor 于建均姚红柯阮晓钢安硕王洋
Owner BEIJING UNIV OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com