OPEN CONTROL SYSTEM ARCHITECTURE FOR MOBILE AUTONOMOUS SYSTEMS

• US 20070112700A1
• Filed: 10/23/2006
• Published: 05/17/2007
• Est. Priority Date: 04/22/2004
• Status: Abandoned Application

• Current Assignee: Frontline Robotics Inc. (Cohort Systems, Inc.)
• Original Assignee: Frontline Robotics Inc. (Cohort Systems, Inc.)
• Inventors: Ballotta, Franco, Den Haan, Albert
• Application Number:
  US11/551,759
• Publication Number:
  US 20070112700A1
• Time in Patent Office: Days
• US Class Current: 706/14
• CPC Class Codes: G05B 2219/39146 Swarm, multiagent, distributed multitask fusion, cooperation multi robots
• CPC Class Codes: G05B 2219/40298 Manipulator on vehicle, wheels, mobile
• CPC Class Codes: G05B 2219/40496 Hierarchical, learning, recognition level controls adaptation, servo level
• CPC Class Codes: G05D 1/024 in combination with a laser lasers per se H01S
• CPC Class Codes: G05D 1/027 comprising intertial navigation means, e.g. azimuth detector inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165
• CPC Class Codes: G05D 1/0272 comprising means for registering the travel distance, e.g. revolutions of wheels measuring distance traversed on the ground by vehicles, e.g. using odometers G01C22/00
• CPC Class Codes: G05D 1/0274 using mapping information stored in a memory device navigation using map-matching G01C21/30
• CPC Class Codes: G05D 1/0278 using satellite positioning signals, e.g. GPS
• CPC Class Codes: G05D 1/0295 by at least one leading vehicle of the fleet
• CPC Class Codes: G05D 1/0297 by controlling means in a control room
• CPC Class Codes: Y02P 90/02 Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

A control system for a mobile autonomous system. The control system comprises a generic controller platform including: at least one microprocessor; and a computer readable medium storing software implementing at least core functionality for controlling autonomous system. One or more user-definable libraries adapted to link to the generic controller platform so as to instantiate a machine node capable of exhibiting desired behaviours of the mobile autonomous system.

Claims

1. A control system for a mobile autonomous system, the control system comprising:

a generic controller platform including;

at least one microprocessor; and

a computer readable medium storing software implementing at least core functionality for controlling autonomous system; and

one or more user-definable libraries adapted to link to the generic controller platform so as to instantiate a machine node capable of exhibiting desired behaviours of the mobile autonomous system.

2. A control system as claimed in claim 1, wherein the machine node instantiated by the linked generic controller platform and user-definable libraries comprises:

a Director layer implementing high level reactive planning;

an Executive layer implementing sensor data processing and low level reflexive operations; and

a communications bus for mediating message flows between the Director layer an Executive layer processes.

3. A control system as claimed in claim 2, wherein processes of the Director layer and executive layer operate in respective different run-time environments.

4. A control system as claimed in claim 2, wherein the Director layer comprises;

at least one reasoning engine adapted for high-level reactive planning, and for generating director commands for execution be the executive layer; and

a dispatcher for managing message flows between the director layer and the executive layer.

5. A control system as claimed in claim 4, wherein the at least one reasoning engine comprises:

a team-OPRS adapted to maintain at least a world view and a listing of team-goals;

a self-OPRS adapted to update the world view based on state data received from the executive layer, and further to update a listing of self-goals based on team-goals recieved from the team-OPRS.

6. A control system as claimed in claim 5, wherein the self-OPRS is further operative to generate the director commands based on the listing of self-goals.

7. A control system as claimed in claim 2, wherein processes of the executive layer execute in a real-time environment.

8. A control system as claimed in claim 2, wherein the executive layer comprises:

a data path for deriving state data indicative of a state of the machine node, based on sensor data from one or more sensor publishing devices; and

a control path for generating actuator control signals based on director commands from the director layer processes and the state data.

9. A control system as claimed in claim 8, wherein the data path comprise:

an input interface for receiving sensor data from one or more sensor publishing devices;

a sensor fusion engine for processing the senor data to derive state data indicative of a state of the machine node; and

a state buffer for storing the state data.

10. A control system as claimed in claim 9, wherein the input interface comprises:

a physical interface;

one or more device driver components for controlling each sensor publishing device; and

one or more perception components for extracting sensor data from messages received by the input interface from each sensor publishing device.

11. A control system as claimed in claim 9, wherein the sensor fusion engine comprises any one or more of:

a Pre-filtering/Diagnostics sub-module;

a Filtering sub-module;

an Obstacle Detecton sub-module; and

a Gate Recognition sub-module.

12. A control system as claimed in claim 11, wherein the Pre-filtering/Diagnostics sub-module is operative to compare first sensor data from a first sensor publishing device with at least second sensor data from a second sensor publishing device, so as to identify errored sensor data.

13. A control system as claimed in claim 12, wherein the Pre-filtering/Diagnostics sub-module is further operative to compare the first sensor data with corresponding expected sensor data based on action commands related to low level actions taken by the machine node.

14. A control system as claimed in claim 11, wherein the Filtering sub-module implements a Kalman filter for estimating a state of the machine node based on the sensor data.

15. A control system as claimed in claim 11, wherein the Obstacle Detection sub-module is operative to detect objects within a predefined avoidance zone proximal the machine node, based on the sensor data.

16. A control system as claimed in claim 11, wherein the Obstacle Detection sub-module is operative to detect objects within a predefined stopping zone proximal the machine node, based on the sensor data.

17. A control system as claimed in claim 11, wherein the Gate Recognition sub-module is operative to detect a location and orientation of a gate, based on the sensor data.

18. A control system as claimed in claim 17, wherein the Gate Recognition sub-module is operative to:

examine each pair of objects detected within a vicinity of the machine node to identify pairs of objects having a predetermined size and separation distance, within respective predetermined tolerances;

examine each identified pair of objects to identify an object pair that is closest to an expected geographical location and orientation of the gate, based on world model information provided by the Director layer; and

calculate a gate signature for the identified object pair.

19. A control system as claimed in claim 18, wherein the gate signature is an n-dimensional vector representative of at least dimensions of the gate.

20. A control system as claimed in claim 8, wherein the control path comprises:

an executive engine responsive to director commands from the director layer, for determining low level actions to be taken by the machine node, and for generating corresponding low-level action commands;

a reflex engine for modifying the low-level action commands in accordance with at least the state data, and generate corresponding action commands; and

a device controller responsive to the action commands, for generating corresponding control signals for each of a plurality of actuators of the machine node.

21. A control system as claimed in claim 20, wherein the reflex engine comprises any one or more of:

a way-point navigation reflex;

an obstacle avoidance reflex; and

a gate crossing reflex.

22. A control system as claimed in claim 21, wherein the way-point navigation reflex comprises any one or more of:

a high level reflex for verifying that a current segment of a path has expired, and loading geographical coordinates of a next way-point of the path;

an Intermediate level reflex for determining a necessity of a consistent turn depending on an angle between two consecutive path segments and the current vehicle orientation, and for managing an angle of approach to a next segment depending on current lateral and heading offsets from the segment; and

a Low level reflex for generating corrective signals to turn the autonomous system depending on current estimations of the lateral and heading offsets from the next segment.

23. A control system as claimed in claim 21, wherein the Obstacle Avoidance reflex is operative for force a deviation of the path around an object detected within a predetermined avoidance zone in a vicinity of the autonomous system.

24. A control system as claimed in claim 23, wherein the Obstacle Avoidance reflex is operative to:

identify, from objects detected within the avoidance zone, a closest object to the autonomous system;

determining a manoeuvre for avoiding the identified closest object; and

forcing execution of the determined manoeuvre.

25. A control system as claimed in claim 21, wherein the Obstacle Avoidance reflex is operative for force a vehicle stop to prevent a collision between the autonomous system and an object detected within a predetermined stopping zone in a vicinity of the autonomous system.

26. A control system as claimed in claim 25, wherein the Obstacle Avoidance reflex is operative to:

detect, an object entering the stopping zone; and

issuing a vehicle stop command.

27. A control system as claimed in claim 1, wherein the generic controller platform further implements core functionality for communicating with other members of a team of robots.

28. A control system as claimed in claim 1, wherein the one or more user-definable libraries implement a structured format for defining data components, device drivers, and logic governing behaviours of the autonomous system.

29. In a control system for a mobile autonomous system, a method of detecting a gate comprising steps of:

examining each pair of objects detected within a vicinity of the autonomous system to identify pairs of objects having a predetermined size and separation distance, within respective predetermined tolerances;

examining each identified pair of objects to identify an object pair that is closest to an expected geographical location and orientation of the gate, based on world model information provided by the Director layer; and

calculating a gate signature for the identified object pair.

30. A method as claimed in claim 29, wherein the gate signature is an n-dimensional vector representative of at least dimensions of the gate.

31. In a control system for a mobile autonomous system, a method of avoiding an object, the method comprising steps of:

identifying, from objects detected within a predetermined avoidance zone of the autonomous system, a closest object to the autonomous system;

determining a manoeuvre for avoiding the identified closest object; and

forcing execution of the determined manoeuvre.