Apparatus and method for enabling rapid configuration and reconfiguration of a robotic assemblage

• US 9,656,389 B2
• Filed: 12/07/2015
• Issued: 05/23/2017
• Est. Priority Date: 02/19/2011
• Status: Active Grant

• Current Assignee: Richard A. Skrinde
• Original Assignee: Richard A. Skrinde
• Inventors: Skrinde, Richard A.
• Primary Examiner(s): Tran, Dalena
• Application Number:
  US14/961,169
• Publication Number:
  US 20160082589A1
• Time in Patent Office: 533 Days
• Field of Search: 700245, 700246, 700250, 700253, 172 2, 172 3, 701 50, 483 8, 483 10, 134 18, 134 56 R, 134 57 R
• CPC Class Codes: B08B 9/049 having self-contained propelling means for moving the cleaning devices along the pipes , i.e. self-propelled
• CPC Class Codes: B25J 11/008 Manipulators for service tasks
• CPC Class Codes: B25J 11/0085 Cleaning
• CPC Class Codes: B25J 3/00 Manipulators of master-slave type, i.e. both controlling unit and controlled unit perform corresponding spatial movements
• CPC Class Codes: B25J 9/0084 comprising a plurality of manipulators
• CPC Class Codes: B25J 9/08 characterised by modular constructions
• CPC Class Codes: B25J 9/163 learning, adaptive, model based, rule based expert control
• CPC Class Codes: B25J 9/1661 characterised by task planning, object-oriented languages
• CPC Class Codes: B25J 9/1676 Avoiding collision or forbidden zones
• CPC Class Codes: B25J 9/1689 Teleoperation
• CPC Class Codes: F16L 2101/12 Cleaning
• CPC Class Codes: F16L 55/32 being self-contained
• CPC Class Codes: Y10S 901/05 Machine driven lead through

Abstract

Modular components form a robotic assembly, the mod-components include modules and tools, each have a set of functions and capabilities, are rapidly configured-reconfigured to function cooperatively, creating a configurable robotic assemblage. Each mod-component incorporates a standardized connector mating with any other standardized connector in an interchangeable manner providing mechanical stability, power, and signals therebetween. Each mod-component incorporates a processor, data storage for mod-component identity, status, and programmable functionality, and for responding to commands. Storage is reprogrammed while the robot is operational, altering both commands and responses. After interconnection, inter-module power and communication are established and each modular component identifies itself and its functionality, thereby providing “plug and play” configuration.

Claims

1. A method, comprising:

storing pre-generated solution and control commands in a data store of an autonomous robotic assemblage as an intelligently instrumented command hierarchy defining a work plan describing a job to exploit a work surface by the autonomous robotic assemblage;

self-optimizing the job performance by autonomously performing the following operations by a control unit of said autonomous robotic assemblage

self-executing at least a first pre-generated set of commands to perform at least a first autonomous operation,

self-modeling at least a first autonomous job performance status,

dynamically transforming the first pre-generated set of commands into at least a first more-optimized set of commands based on the self-modeled first autonomous job performance status and the job'"'"'s description described in the work plan,

self-executing the first more-optimized set of commands to perform at least a second autonomous operation, and

self-resolving at least a first fault for at least one of system errors and assemblage collisions involving internal articulators or with external objects while the second autonomous operation is being performed; and

providing tele-operated supervision of at least one autonomous command.

2. The method according to claim 1, wherein said autonomous robotic assemblage comprises

a robot or other mechanized system incorporating automatable procedures, and

at least one module that has at least one of (a) a standardized interface to external systems and (b) an embedded controller employing at least one tier of distribution and incorporating at least one computer.

3. The method according to claim 1, further comprising performing at least one of the following operations by an operations interface to manage said autonomous robotic assemblage'"'"'s self-optimization:

supervising autonomous activities;

monitoring status of operational performance; and

supporting tele-operated training and manual override.

4. The method according to claim 1, further comprising performing operations by a multi-dimensional virtual environment to self-model operational status and performance efficiency based on at least one event detected from at least one of the following:

said autonomous robotic assemblage internal and external operating conditions;

state of said autonomous robotic assemblage articulation and position;

work surface conditions;

surrounding work area conditions;

the work plan; and

data stores supporting the work plan.

5. The method according to claim 1, further comprising performing an autonomous resolution of at least one operations error.

6. The method according to claim 1, wherein said intelligently instrumented command hierarchy adapts to environmental circumstances and changing work conditions during at least a first operation of the autonomous robotic assemblage based on

at least a first solution command coordinating and synchronizing at least a first particular behavior, and

at least a first control command distributing said solution command by real-time reformatting into at least a first translation communicating with at least a first functional component of said robotic assemblage, and conversely, acquiring status through the intelligent closed-loop sensing of at least a first internal and external experience of said functional component.

7. The method according to claim 1, further comprising self-optimizing at least a first solution command so as to form at least a first new rendition based on making at least a first improvement to at least one of the following:

work plan performance as a function of goal and objective attainment;

breadth of autonomous scope and scale; and

resolution of unplanned and unexpected occurrences.

8. The method according to claim 1, further comprising self-optimizing at least a first control command so as to form a new rendition

based on making improvements resultant from at least one of the following:

tele-operated training;

performance prioritizations derived through analysis of operating history and simulations of future potentiality;

as applied to at least one of the following;

the work plan;

solution patterns arising from solution command sets;

status and sensory feedback;

resolved deviations between the expected operational state of a solution command set and the actual operational state of the autonomous robotic assemblage, and any rendition of any of the above.

9. The method according to claim 1, further comprising self-optimizing the collaborative coordination of multiple robotic assemblages to most efficiently perform different aspects of the work plan.

10. The method according to claim 1, further comprising employing expert systems to expand a self-optimizing capability selected from the group consisting of coordinating operations, avoiding collisions, enhancing an operator interface, correcting errors, creating virtual or simulated environments, and improving work plan and job performance.

11. A system, comprising:

a robotic assemblage comprising a storage device in which an intelligently instrumented command hierarchy stores pre-generated solution and control commands that define a work plan, where said work plan describes a job to exploit a work surface by said robotic assemblage;

wherein a control unit of said robotic assemblage is self-configurable to perform the following operations to self-optimize said job performance;

self-executing at least a first pre-generated set of commands to perform at least a first autonomous operation;

self-modeling at least a first autonomous job performance status;

dynamically transforming the first pre-generated set of commands into at least a first more-optimized set of commands based on the self-modeled first autonomous job performance status and the job'"'"'s description described in the work plan;

self-executing the first more-optimized set of commands to perform at least a second autonomous operation; and

self-resolving at least a first fault for at least one of system errors, assemblage collisions involving internal articulators or with external objects while the second autonomous operation is being performed; and

a tele-operation device configured to enable tele-operated supervision of at least one autonomous command.

12. The system according to claim 11, wherein said autonomous robotic assemblage comprises

a robot or other mechanized system incorporating automatable procedures, and

at least one module that has at least one of (a) a standardized interface to external systems and (b) an embedded controller employing at least one tier of distribution and incorporating at least one computer.

13. The system according to claim 11, wherein a control console manages said autonomous robotic assemblage'"'"'s self-optimization operations by at least one of the following:

supervising autonomous activities;

monitoring status of operational performance; and

supporting tele-operated training and manual override.

14. The system according to claim 11, wherein a multi-dimensional virtual environment self-models operational status based on at least one event detected from at least one of the following:

said robotic assemblage internal and external operating conditions;

articulation and positioning;

surrounding work area and work surface conditions;

the work plan; and

content of a data store.

15. The system according to claim 11, wherein an autonomous operation resolves a monitored error.

16. The system according to claim 11, wherein said intelligently instrumented command hierarchy adapts to environmental circumstances and changing work conditions during at least a first operation of the autonomous robotic assemblage based on

at least a first solution command coordinating and synchronizing at least a first particular behavior, and

at least a first control command distributing said solution command by real-time reformatting into at least a first translation communicating with at least a first functional component of said robotic assemblage, and conversely, acquiring status through the intelligent closed-loop sensing of at least a first internal and external experience of said functional component.

17. The system according to claim 11, wherein self-optimizing at least a first solution command so as to form at least a first new rendition based on making at least a first improvement to at least one of the following:

work plan performance as a function of goal and objective attainment;

breadth of autonomous scope and scale;

resolution of unplanned and unexpected occurrences.

18. The system according to claim 11, wherein self-optimizing at least a first control command so as to form a new rendition

based on making improvements resultant from at least one of the following:

tele-operated training;

performance prioritizations derived through analysis of operating history and simulations of future potentiality;

as applied to at least one of the following;

the work plan;

solution patterns arising from solution command sets;

status and sensory feedback;

resolved deviations between the expected operational state of a solution command set and the actual operational state of the autonomous robotic assemblage, and any rendition of any of the above.

19. The system according to claim 11, wherein a collaborative coordination of multiple robotic assemblages are dynamically optimized to perform different aspects of the work plan.

20. The system according to claim 11, wherein expert systems are employed to expand a self-optimizing capability selected from the group consisting of coordinating operations, avoiding collisions, enhancing an operator interface, correcting errors, creating virtual or simulated environments, and improving work plan performance.