Syntactic inferential motion planning method for robotic systems

• US 9,855,657 B2
• Filed: 01/30/2004
• Issued: 01/02/2018
• Est. Priority Date: 01/31/2003
• Status: Active Grant

• Current Assignee: Thermo CRS Ltd. (Thermo Fisher Scientific Incorporated)
• Original Assignee: Thermo CRS Ltd. (Thermo Fisher Scientific Incorporated)
• Inventors: McCrackin, Daniel Curtis, Johnson, Stephen Wayne
• Primary Examiner(s): Nguyen, Bao Long T
• Application Number:
  US10/543,853
• Publication Number:
  US 20070005179A1
• Time in Patent Office: 5,086 Days
• Field of Search: 700245, 700213, 700246, 700249, 701 23, 701117, 701118, 701119, 701213, 701214, 701215, 701221, 701208, 701226, 701301, 3409951, 34053913, 34053917, 340903, 340905, 34099513, 34235703, 34235708, 3423571, 34235706, 34235713, 34235714, 342457, 382128, 382224, 382154, 382285, 180167
• CPC Class Codes: B25J 9/163 learning, adaptive, model based, rule based expert control
• CPC Class Codes: B25J 9/1666 Avoiding collision or forbidden zones
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem

Abstract

A method and system for planning and optimizing the movement of a robotic device comprises establishing a plurality of spatial locations where the device can possibly be positioned and establishing rule sets for constraining movement of the robotic device between the locations. Once a start and end point have been determined, the method of the invention calculates all possible routes for the device to move, via the established locations and following the constraints of the rule sets. The calculated routes are then compared to a criteria, such as minimizing time, and an optimum route, meeting the desired criteria is determined. The calculated routes may also be cached for future access. The invention also provides for an error recovery method for allowing a robotic device to recover should it encounter an error.

Claims

1. A method for planning the motion of a robot, comprising:

a) defining a plurality of robot end effector locations, in terms of a spatial coordinate system, including a start location, an end location, and at least one other programmed point;

b) storing said locations in a computer memory;

c) defining a set of rules for governing movement of said robot end effector between said locations;

d) storing said set of rules in the computer memory;

e) calculating, by a processor, two or more possible routes from said start location to said end location;

f) determining, by said processor, from said two or more possible routes, an optimized route, from said start location to said end location, which meets a predetermined criteria; and

g) enabling, in response to said determination of said optimized route which meets the predetermined criteria, movement of said robot end effector along said optimized route from said start location to said end location by way of the at least one other programmed point such that each point-to-point move obeys the set of rules.

2. The method of claim 1 wherein said locations include at least one terminal location at which the robot end effector interacts with an object.

3. The method of claim 2 wherein said locations include safe positions of said robot end effector;

and transit positions of said robot end effector.

4. The method of claim 1 wherein said locations include at least one safe location at which the robot end effector is safely positioned out of the way of a proximate piece of equipment.

5. The method of claim 4 wherein said locations include object engagement or release positions of said robot end effector;

and transit positions of said robot end effector.

6. The method of claim 1 wherein said set of rules comprises conditions of movement of said robot end effector between adjacent pairs of said locations.

7. The method of claim 1 wherein, in step (e), all possible routes between said start and end locations are calculated, said routes comprising a sequence of locations.

8. The method of claim 1 wherein, in step (f), the predetermined criteria comprises a minimized travel time of said robot end effector between said start and end locations.

9. The method of claim 8 wherein said step (f) comprises the sub-steps of:

i) finding all minimum-length routes that take the robot end effector from the start location to the end location; and

,

ii) choosing from said minimum-length routes of step (i), the route having the shortest travel time from said start location to end location.

10. The method of claim 1 wherein said rules comprise at least one path, said path comprising two or more of said locations arranged in a preset order and wherein movement of said robot end effector between locations on said paths is constrained to said preset order.

11. The method of claim 1 wherein said rules comprise at least one region, said region comprising two or more of said locations arranged in a grouping and wherein said robot end effector is permitted to move freely within said region.

12. The method of claim 1 wherein said rules comprise at least one path and at least one region, said path comprising two or more of said locations arranged in a preset order and wherein movement of said robot end effector between locations on said paths is constrained to said preset order, and said region comprising two or more of said locations arranged in a grouping and wherein said robot end effector is permitted to move freely within said region.

13. The method of claim 12 wherein, in step (e) of the method, all possible routes between said start and end locations are calculated, said routes comprising a sequence of locations.

14. The method of claim 13 wherein, in step (f), the predetermined criteria comprises a minimized travel time of said robot end effector between said start and end locations.

15. The method of claim 12, wherein said method includes an error resolving algorithm wherein the robot resolves location when an error condition is encountered.

16. The method of claim 15 wherein said error resolving algorithm results in the robot end effector being assigned to a nearest one of said locations.

17. The method of claim 16 wherein the robot end effector is assigned to the nearest one of said locations by the steps of:

choosing a minimum distance limit;

calculating the distance of said robot end effector from each of said locations;

identifying the nearest location to said robot end effector, said nearest location having the shortest distance from said robot end effector;

comparing said shortest distance to said distance limit; and

where said shortest distance is less than or equal to said distance limit, assigning the robot end effector to said nearest location.

18. The method of claim 17 wherein, where said shortest distance is more than said distance limit, the method further comprising the steps of:

assigning a weighting factor, M, to each path and region;

calculating the shortest distance, D, from the robot end effector to each line joining said locations in said paths and regions;

dividing said shortest distances by the weighting factor to provide weighted distances, D/M;

identifying the line segment with the smallest weighted distance D/M;

comparing the smallest weighted distance, D/M, with said minimum distance limit;

if the weighted distance for the identified line segment is less than the minimum distance limit, assigning the robot end effector to said identified line segment;

calculating the distance of the robot end effector to the end points of said identified line segment; and

moving said robot end effector to the closest of said end points and assigning the robot end effector to the location occupied by the closest of said end points.

19. The method of claim 15 wherein said error resolving algorithm comprises the steps of:

choosing a minimum distance limit;

assigning a weighting factor, M, to each path and region;

calculating the shortest distance, D, from the robot end effector to each line joining said locations in said paths and regions;

dividing said shortest distances by the weighting factor to provide weighted distances, D/M;

identifying the line segment with the smallest weighted distance D/M;

comparing the smallest weighted distance, D/M, with said minimum distance limit;

if the weighted distance for the identified line segment is less than the minimum distance limit, assigning the robot end effector to said identified line segment;

calculating the distance of the robot end effector to the end points of said identified line segment; and

moving said robot end effector to the closest of said end points and assigning the robot end effector to the location occupied by the closest of said end points.

20. The method of claim 12 wherein said step (f) comprises the sub-steps of:

i) finding all minimum-length routes that take the robot end effector from the start location to the end location; and

ii) choosing from said minimum-length routes of step (a), the route having the shortest travel time from said start location to end location.

21. The method of claim 1, wherein said method includes an error resolving algorithm wherein the robot resolves location when an error condition is encountered.

22. The method of claim 21 wherein said error resolving algorithm results in the robot end effector being assigned to a nearest one of said locations.

23. The method of claim 22 wherein the robot end effector is assigned to the nearest one of said locations by the steps of:

choosing a minimum distance limit;

calculating the distance of said robot end effector from each of said locations;

identifying the nearest location to said robot end effector, said nearest location having the shortest distance from said robot end effector;

comparing said shortest distance to said distance limit; and

where said shortest distance is less than or equal to said distance limit, assigning the robot end effector to said nearest location.

24. The method according to claim 1 wherein optimized routes between pairs of locations are cached in the computer memory and made searchable.

25. The method of claim 24 wherein, upon entering a start location and an end location, the computer memory is searched for previously determined optimized paths.

26. The method of claim 1, wherein the spatial coordinate system is a joint coordinate system, a motor coordinate system, a Cartesian coordinate system or a cylindrical coordinate system.

27. A controller for a robot, the controller comprising a processor and a computer memory, wherein the processor is configured to:

define a plurality of robot end effector locations, in terms of a spatial coordinate system, including a start location, an end location, and at least one other programmed point;

store said locations in the computer memory;

define a set of rules for governing movement of said robot end effector between said locations;

store said set of rules in the computer memory;

calculate two or more possible routes from said start location to said end location;

determine from said two or more possible routes, an optimized route, from said start location to said end location, which meets a predetermined criteria; and

enable, in response to said determination of said optimized route which meets the predetermined criteria, movement of said robot end effector along said optimized route from said start location to said end location by way of the at least one other programmed point such that each point-to-point move obeys the set of rules.