Architecture and Interface for a Device-Extensible Distributed Navigation System

• US 20120089292A1
• Filed: 02/12/2011
• Published: 04/12/2012
• Est. Priority Date: 02/14/2010
• Status: Abandoned Application

• Current Assignee: Leonid Naimark, Marcos Antonio Bergamo, William H. Weedon III
• Original Assignee: Leonid Naimark, Marcos Antonio Bergamo, William H. Weedon III
• Inventors: Naimark, Leonid, Weedon, William H. III, Bergamo, Marcos Antonio
• Application Number:
  US13/026,226
• Publication Number:
  US 20120089292A1
• Time in Patent Office: Days
• US Class Current: 701/23
• CPC Class Codes: G01C 21/165 combined with non-inertial navigation instruments
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G05D 1/0246 using a video camera in combination with image processing means
• CPC Class Codes: G05D 1/0257 using a radar radar systems designed for anti-collision purposes between land vehicles or between land vehicle and fixed obstacles G01S13/931
• 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

Abstract

A method for navigating a moving object (vehicle) utilizing a Navigation manager module and comprising the steps of: communicating with all sensors, processing units, mission manager and other vehicles navigation managers; configuring and reconfiguring sensors based on mission scenario objectives, in-vehicle and global constraints; sensor grouping according to relationship to the vehicle and environment, where an entire sensor group is seen by navigation manager as a single sensor; processing unit containing Update Filter; and a dynamically updated API database.

Claims

1. A method for navigating a moving object (vehicle) utilizing a Navigation manager module and comprising the steps of:

Communicating with all sensors, processing units, mission manager and other vehicles navigation managers;

Configuring and reconfiguring sensors based on mission scenario objectives, in-vehicle and global constraints;

Sensor grouping according to relationship to the vehicle and environment, where an entire sensor group is seen by navigation manager as a single sensor;

Processing unit containing Update Filter; and

,

Dynamically updated API database.

2. The method of claim 1, wherein said sensors are grouped into three groups according to:

relationship to the vehicle, environment and locality of the reference coordinate system.

3. The method of claim 2, wherein said update filter processing is separated into two channels:

one with fixed number of states representing single point-vector on a vehicle;

another with limited number of states representing local environment based on local processing and network throughput capabilities.

4. The method of claim 2, wherein said sensors can be comprised of different types including sensor-vehicle interaction and are supported through dynamically updated API database.

5. The method of claim 4, wherein said dynamical API database occurs before start of the mission.

6. The method of claim 4, wherein said dynamical API database occurs during the mission through network communication.

7. The method of claim 4, wherein said sensors are calibrated and recalibrated upon receiving calibration command from said Navigation manager module through said dedicated API.

8. The method of claim 4, wherein said sensors are turned off and on upon receiving on/off command from said Navigation manager module through said API.

9. The method of claim 3, wherein said vehicle is autonomous rigid vehicle.

10. The method of claim 3, wherein said vehicle is flexible vehicle (human), while each joint of said human vehicle is considered as rigid vehicle constrained by connections between joints.

11. The method of claim 3, wherein said vehicle is distributed rigid or flexible vehicle, with partially known and exchanged through network communication coordinates relationship between corresponding rigid vehicles.

12. The method of claim 4 wherein said sensor processing interface is simplified through abstractions and objects that include conversion of sensor measurement specifics into processing-common navigation objects.

13. The method of claim 12 wherein said sensors are distributed in each of three groups and can be mixed, selected and matched by processing according to their utility for the navigation.

14. The method of claim 13 wherein said three sensor groups are Vehicle-Referenced (VR) Sensors Group, Global (coordinates) Sensors Group (GSG) and Environment Features (EF) Sensing Group.

15. The method of claim 14, wherein each of 3 sensor groups

Communicates as single sensor through API with Navigation Manager;

Contains dynamic low-level API database;

Contains either Vehicle Sensor Map or Vehicle Feature Map or Distributed Vehicle Sensor Map;

Contains Timing Synchronizer;

Contains Measurement Merger; and

Contains vehicle Sensor calibration manager or Vehicle Feature Calibration manager.

16. The method of claim 15, wherein said Timing Synchronizer is allowed to send simultaneous or alternating measurement request to different sensors.

17. The method of claim 15, wherein said Measurement Merger merges measurements obtained from sensors through Timing Synchronizer, while adding, interpolating or extrapolating such measurements to achieve single rate output from each sensor group.

18. The method of claim 14, wherein said Environment Features (EF) Sensing Group has said Distributed-Vehicle Sensor Map formation functionality through said API network exchange with other vehicles.

19. The method of claim 18, wherein said Features (EF) Sensing Group Measurement Merger comprises:

Object Generator;

Object States Selector;

Measurements Selector; and

Coordinates Converter.

20. The method of claim 19, wherein said Object Generator has an ability to form multi-sensor-multi-feature objects according to Object Generation rules.

21. The method of claim 3 wherein said number of states update filter operates with single or dual rate;

and limited number of states update filter operates with single rate.

22. The method of claim 21 wherein said fixed number of states update filter is an Extended Kalman Filter and limited number of states update filter is particle filter.

23. The method of claim 20 where Local Environment Map is constructed and updated, based upon only environmental features, currently senses by all sensors on distributed vehicle.

24. The method of claim 23 wherein an additional functionality of converting Local Maps in claim 23 into Global Environment map to achieve Simultaneous Localization and Mapping Capability (SLAM).