NATURAL MACHINE INTERFACE SYSTEM

• US 20170343992A1
• Filed: 08/21/2017
• Published: 11/30/2017
• Est. Priority Date: 07/09/2012
• Status: Active Grant

• Current Assignee: Deep Learning Robotics LTD
• Original Assignee: Deep Learning Robotics LTD
• Inventors: BENAIM, Carlos, REINER, Miriam
• Granted Patent: US 10,571,896 B2
• Time in Patent Office: Days
• CPC Class Codes: G05B 19/4061 Avoiding collision or forbidden zones
• CPC Class Codes: G05B 19/4183 characterised by data acquisition, e.g. workpiece identification
• CPC Class Codes: G06F 30/00 Computer-aided design [CAD]
• CPC Class Codes: G06V 40/28 Recognition of hand or arm movements, e.g. recognition of deaf sign language static hand signs G06V40/113
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

A method for defining a robotic machine task. The method comprises a) collecting a sequence of a plurality of images showing at least one demonstrator performing at least one manipulation of at least one object, b) performing an analysis of said sequence of a plurality of images to identify demonstrator body parts manipulating said at least one object and said at least one manipulation of said at least one object, c) determining at least one robotic machine movement to perform said task, and d) generating at least one motion command for instructing said robotic machine to perform said task.

Claims

1. A method for enhancing at least one robotic machine'"'"'s design, comprising:

using at least one processor to execute code instructions for;

gathering usage data of a plurality of technical elements from at least one robotic machine while said at least one robotic machine performs at least one task;

analyzing, using statistical analysis, said usage data to determine at least one desired parameter for each of said plurality of said technical elements; and

generating a new design of said at least one robotic machine using said at least one desired parameter of each of said plurality of technical elements, said new design defines at least one change to a current design of said at least one robotic machine.

2. The method of claim 1, wherein said at least one change is a change to robotic machine'"'"'s hardware.

3. The method of claim 1, wherein said at least one change is a change to robotic machine'"'"'s software.

4. The method of claim 1, wherein said at least one change is a change to robotic machine'"'"'s processing algorithm

5. The method of claim 1, wherein said usage data is acquired by at least one controller associated with said at least one robotic machine, through analysis of at least one sequence of a plurality of images collected by at least one spatial sensor, said at least one sequence of said plurality of images depicts said at least one robotic machine performing said at least one task.

6. The method of claim 1, wherein said usage data is acquired by at least one controller associated with said at least one robotic machine, through robotic machine movement history.

7. The method of claim 1, wherein said usage data is software usage.

8. The method of claim 1, wherein said at least one desired parameter is any combination of robotic machine'"'"'s cost, maintenance cost, speed of performing task, precision of performing task, weight, dimensions, strength, power consumption, throughput, and other unspecified production relevant parameter.

9. The method of claim 5, wherein said at least one spatial sensor is at least one depth map sensor.

10. The method of claim 5, wherein said at least one spatial sensor is at least one digital camera.

11. The method of claim 1, wherein said robotic machine design'"'"'s is software design.

12. The method of claim 1, wherein said robotic machine design'"'"'s is hardware design.

13. An apparatus associated with at least one robotic machine comprising:

at least one spatial sensor for collecting a sequence of a plurality of images depicting at least one associated robotic machine performing at least one task;

at least one processing unit which analyses said sequence of said plurality of images collected by said at least one spatial sensor, to identify at least one technical usage characteristic of said at least one associated robotic machine during said performance of said at least one task;

at least one storage unit to save said sequence of said plurality of images and said at least one technical usage characteristic;

at least one digital communication method to communicate said at least one technical usage characteristic to at least one statistical analysis system; and

a housing for containing said at least one spatial sensor, said at least one processing unit, said storage unit, and said communication method, said housing being configured for being suitable for an environment of said at least one associated robotic machine.

14. The apparatus of claim 13, wherein said at least one spatial sensor consists of at least one depth map sensor.

15. The apparatus of claim 13, wherein said at least one spatial sensor consists of at least one digital camera.

16. The apparatus of claim 13, wherein said at least one digital communication method is a member of a group consisting of wired Ethernet, wireless Ethernet, serial communication standards, parallel communications standards, infrared communications, wired universal serial bus, wireless universal serial bus and Bluetooth communication.