Work assisting system including machine learning unit

• US 10,603,793 B2
• Filed: 10/06/2017
• Issued: 03/31/2020
• Est. Priority Date: 10/07/2016
• Status: Active Grant

• Current Assignee: Fanuc Corporation
• Original Assignee: Fanuc Corporation
• Inventors: Ooba, Masafumi
• Primary Examiner(s): Nguyen, Bao Long T
• Application Number:
  US15/726,818
• Publication Number:
  US 20180126558A1
• Time in Patent Office: 907 Days
• Field of Search: 700245, 700179, 700246, 700253, 706 12, 483 1
• CPC Class Codes: B25J 13/089 Determining the position of the robot with reference to its environment
• CPC Class Codes: B25J 19/06 Safety devices
• CPC Class Codes: B25J 9/161 Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
• CPC Class Codes: B25J 9/163 learning, adaptive, model based, rule based expert control
• CPC Class Codes: B25J 9/1694 characterised by use of sensors other than normal servo-feedback from position, speed or acceleration sensors, perception control, multi-sensor controlled systems, sensor fusion
• CPC Class Codes: G05B 19/4183 characterised by data acquisition, e.g. workpiece identification
• CPC Class Codes: G05B 19/423 Teaching successive positions by walk-through, i.e. the tool head or end effector being grasped and guided directly, with or without servo-assistance, to follow a path
• CPC Class Codes: G05B 2219/40198 Contact with human allowed if under pain tolerance limit
• CPC Class Codes: G05B 2219/40202 Human robot coexistence
• CPC Class Codes: G05B 2219/40409 Robot brings object near operator, operator places object in correct position
• CPC Class Codes: G06N 3/08 Learning methods
• CPC Class Codes: G06V 40/11 Hand-related biometrics; Hand pose recognition

Abstract

A work assisting system includes a sensor unit that detects a position and an orientation of at least one body part of a worker; a supply unit that supplies a part or a tool to the worker; and a cell controller that controls the supply unit, the cell controller including a machine learning unit that constructs a model by learning a work status of the worker on the basis of the detected position and orientation, and a work status determining unit that determines the work status of the worker by using the constructed model. The supply unit selects the part or tool on the basis of the determined work status and changes the position and orientation of the part or tool on the basis of the position and orientation of the at least one body part.

Claims

1. A work assisting system comprising:

a sensor unit that detects a position and an orientation of each of the body parts including a hand of a worker;

a supply unit that supplies a part or a tool to the worker; and

a cell controller that controls the supply unit, the cell controller comprising;

a machine learning unit that constructs a learning model based on the detected position and orientation of the each of the body parts and a label relating to a work status of the worker, and

a work status determining unit that determines the work status of the worker by using the constructed learning model,

wherein the supply unit selects the part or tool based on the determined work status and a work table in which the labeled work status is correlated to a motion of the supply unit, and changes a position and orientation of the part or tool based on the position and orientation of the each of the body parts.

2. The work assisting system according to claim 1, wherein the model constructed in the machine learning unit is shared with another cell controller connected to the cell controller via a network.

3. The work assisting system according to claim 1, wherein the supply unit includes a robot.

4. The work assisting system according to claim 1, wherein the machine learning unit includes a neural network.

5. The work assisting system according to claim 1, wherein the supply unit changes the position and orientation of the part or tool so that a coordinate system preset for each of the part or tool is coincident with a coordinate system that indicates the position and orientation of the each of the body parts.

6. The work assisting system according to claim 1, wherein the machine learning unit constructs the learning model based on data obtained by normalizing the position and orientation of the each of the body parts as learning data, and data obtained by normalizing the work status as the label.