Cloud robot collaborative learning method based on hybrid enhanced intelligence

A collaborative learning and robot technology, applied in the field of human-computer interaction, can solve problems such as not being able to train new tasks, and achieve the effect of shortening the learning time

Inactive Publication Date: 2018-07-27
SOUTH CHINA UNIV OF TECH
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, if you want a robot to master multiple skills and adapt to multiple environments, you should not train each skill in each environment from scrat

Method used

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  • Cloud robot collaborative learning method based on hybrid enhanced intelligence
  • Cloud robot collaborative learning method based on hybrid enhanced intelligence
  • Cloud robot collaborative learning method based on hybrid enhanced intelligence

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Embodiment Construction

[0020] In order to make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be described in detail below with reference to the accompanying drawings and embodiments.

[0021] A cloud robot collaborative learning method based on hybrid enhanced intelligence of the present invention, based on NTP and the human-machine collaboration service framework of cloud robots, realizes the use of multiple robots to learn common skills together. Robots learn mobility skills from experience, share skills from other robots, and learn skills through human assistance. In this framework, it is mainly composed of four parts: cloud robot, local robot, teaching learning and task understanding based on NTP (Neural Task Programming). A local robot is composed of N mutually independent robots. Cloud robot refers to an academic concept of how robot information is stored and acquired, which aggregates and shares dece...

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Abstract

The invention provides a cloud robot collaborative learning method based on hybrid enhanced intelligence. The method comprises the following steps of S1, adopting a meta-learning method of NTP (NeuralTask Programming) for dividing a large task recursion into simple sub-tasks for teaching robots; S2, achieving robot action imitative learning based on a human-computer interaction technology, and teaching the robots about skills; S3, utilizing a self-organizing incremental neural network (SOINN) to gather the scattered robot skills for sharing use. According to the method, multiple robots learnhuman skills separately, then upload learned information into a server and share the information in the server for training and adjustment. Not only can the learning time be greatly shortened, but also the diversity of tasks can be expanded. The robots conduct collaborative learning and transmit experiences to one another through a network (or a cloud robot), that is to say, the robots can learn from one another.

Description

technical field [0001] The invention relates to the field of human-computer interaction, in particular to a cloud robot collaborative learning method based on hybrid enhanced intelligence. Background technique [0002] At present, the main application fields of human-robot collaboration include industrial robots, home service robots, medical robots, rescue robots, and special robots, etc. These fields usually require human participation and leadership to complete relatively complex tasks. In the past, robots often completed some rough tasks first, and then workers completed other difficult and complex tasks on the next assembly line. However, this mode wastes a lot of production time, because some tasks can be completed at the same time; On the one hand, in some tasks, workers can complete tasks more efficiently with the assistance of robots or robots with the assistance of workers. In these production lines, robots can complete some tedious and heavy work, while workers ca...

Claims

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Application Information

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IPC IPC(8): G05B13/04
CPCG05B13/042
Inventor 杜广龙张爱玲张博刘彩冰张平
Owner SOUTH CHINA UNIV OF TECH
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