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Robot autonomous anomaly repair skill learning method and system

A learning method and robot technology, applied in the field of robot skill learning, can solve the problem of lack of consideration of the characteristics of human-machine cooperation system, and achieve the effect of promoting autonomous operation

Pending Publication Date: 2021-02-12
INST OF INTELLIGENT MFG GUANGDONG ACAD OF SCI
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  • Summary
  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

However, traditionally, artificially pre-set rules or relying on the robot's own motion planning method are used to repair robot abnormalities, which lacks consideration of abnormal types and the characteristics of human-machine collaboration systems, and cannot meet the needs of practical applications.

Method used

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  • Robot autonomous anomaly repair skill learning method and system
  • Robot autonomous anomaly repair skill learning method and system
  • Robot autonomous anomaly repair skill learning method and system

Examples

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Embodiment

[0045] see figure 1 , figure 1 A schematic flowchart of a method for learning a robot autonomous abnormal repair skill in an embodiment of the present invention is shown.

[0046] Such as figure 1 As shown, a robot autonomous abnormal repair skill learning method, the method includes:

[0047] S101. Predefine human demonstration trajectories when the robot performs complex tasks;

[0048] The implementation process of the present invention includes: (1) predefining the N motor skills required by the robot when performing complex tasks; (2) using a finite state machine (FSM) to serialize the types and execution orders of the N motor skills, Generate corresponding N motor skill sequences.

[0049] S102. Obtain multi-modal sensing information of the robot when performing the complex task, and use the multi-modal sensing information to monitor and obtain abnormal motor skills;

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Abstract

The invention discloses a robot autonomous anomaly repair skill learning method and system. The method comprises the following steps: pre-defining a human demonstration track when a robot executes a complex task; acquiring multi-modal sensing information of the robot when executing the complex task, and monitoring by utilizing the multi-modal sensing information to acquire an abnormal motion skill; and based on the abnormal state type of the abnormal motion skill, starting an adaptive motion repair strategy to autonomously repair the abnormal motion skill. In the embodiment of the invention, the abnormal types encountered when the robot executes the complex task can be distinguished, and the corresponding repair strategy can be formulated, so that the robot can be promoted to realize longer-term autonomous operation.

Description

technical field [0001] The invention relates to the technical field of robot skill learning, in particular to a method and system for learning robot autonomous abnormal repair skills. Background technique [0002] With the continuous improvement of the breadth and depth of robot applications, the existing intelligent technology cannot meet the needs, and the collaborative operation of humans and robots is the most effective solution. Human-machine collaboration means that robots sense through multiple sensors and cooperate with humans to complete various delicate and complex operational tasks. At present, this method has been widely used in the fields of intelligent manufacturing, logistics warehousing, and medical services. However, in a human-machine collaborative environment, abnormal events such as robot-environment collisions, robot-human collisions, object operation failures, etc. will occur due to robot program errors, sensor noise, and human misoperations. Harm to h...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N20/00
CPCG06N20/00
Inventor 吴鸿敏徐智浩周雪峰程韬波鄢武苏泽荣
Owner INST OF INTELLIGENT MFG GUANGDONG ACAD OF SCI
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