System and method for localizing two or more moving nodes

• US 9,746,330 B2
• Filed: 06/09/2015
• Issued: 08/29/2017
• Est. Priority Date: 08/03/2013
• Status: Active Grant

• Current Assignee: Robotic Research OPCO LLC
• Original Assignee: Robotic Research LLC
• Inventors: Lacaze, Alberto Daniel, Murphy, Karl, Smith, Kyle
• Primary Examiner(s): EL CHANTI, HUSSEIN A
• Application Number:
  US14/734,014
• Publication Number:
  US 20160025502A1
• Time in Patent Office: 812 Days
• Field of Search: 701454
• CPC Class Codes: G01C 21/20 Instruments for performing navigational calculations G01C21/24, G01C21/26 take precedence
• CPC Class Codes: G01S 19/51 Relative positioning
• CPC Class Codes: G01S 5/0284 Relative positioning
• CPC Class Codes: G01S 5/0289 of multiple transceivers, e.g. in ad hoc networks
• CPC Class Codes: G08B 13/19608 Tracking movement of a target, e.g. by detecting an object predefined as a target, using target direction and or velocity to predict its new position

Abstract

UMAPS is a multifaceted system that can be robot-mounted, human-worn, or canine carried. UMAPS produces real-time, 3D mapping and localization for the user as they move throughout a GPS-denied environment (e.g. buildings, caves, or tunnels). An Operator Control Unit (OCU) displays information collected by UMAPS; 2D floorplans; 3D textured-enriched surfaces of the structure'"'"'s interior; and the location of the users within that structure. UMAPS has an open architecture that allows it to function with any OCU. UMAPS has three distinct subsystems: obstacle maps for robot mobility, mapping, and positioning.

Claims

1. A program storage device readable by a computer machine, tangibly embodying program instructions executable by the computer machine to perform method steps for a method for distributing and localizing two or more moving nodes, the method steps comprising:

providing inertial components on two or more moving nodes;

measuring positional relationships between two or more moving nodes;

providing a communications network;

enabling communication between nodes;

providing and associating a computational device with each node;

making positional relationship measurements by the computational device with each node using the inertial components;

obtaining measurements one at a time, using time-of-arrival and changes in position, provided by a local inertial navigation unit of a moving node;

providing a filtering algorithm for the computational device of each node;

determining, by the filtering mechanism for the computational device of each node, the position of the nodes using the inertial measurements and the positional relationship measurements;

creating a spring network among the nodes; and

using the springs to pull position and navigation solutions to a more accurate location.

2. The method of claim 1, further comprising step of:

encoding absolute and relative measurements into a partial constraint.

3. The method of claim 1, further comprising the steps of:

co-locating one or more mapping sensors co-located with one or more nodes; and

building a map from the mapping sensors, relationship measurements, inertial measurements, and filtering mechanism.

4. The method of claim 1, further comprising the step of:

determining the positional relationship between nodes using ranging radios located between the nodes.

5. The method of claim 1, further comprising the step of:

measuring the positional relationship between nodes using wireless ranging between nodes.

6. The method of claim 1, further comprising the step of:

co-locating a GPS receiver at one or more node locations.

7. The method of claim 1, further comprising the steps of:

placing an anchor node at a point with a known location; and

using the location of the anchor node by the filtering mechanism.

8. The method of claim 1, further comprising the steps of:

placing nodes at one or more arbitrary points that will be visited in multiple instances; and

determining, by the filtering mechanism, the location of a point and therefore the location of the nodes when the nodes were at the point.

9. The method of claim 1, further comprising the steps of:

co-locating one or more sensors at one or more nodes that can detect the positional relationship to one or more features in the surroundings, where the location of a feature is known to some accuracy;

detecting one or more features in the surroundings by the co-located sensors;

determining the positional relationship to the feature and the position and accuracy of the feature; and

aiding in determining node positions by the filtering mechanism.

10. The method of claim 1, further comprising the steps of:

co-locating one or more sensors with one or more nodes;

detecting the positional relationship to one or more features in the surroundings;

calculating the positional relationship of the node to the one or more features in the surroundings;

using the positional relationship to the feature from multiple passes of the same node by the filtering mechanism; and

determining node position.

11. The method of claim 1, further comprising the steps of:

co-locating one or more sensors with one or more nodes that can detect the positional relationship to one or more features in the surroundings;

calculating the positional relationship of a node to the one or more features in the surroundings;

using the positional relationship to the feature from multiple passes of multiple nodes by the filtering mechanism; and

determining node position.

12. The method of claim 1, further comprising the steps of:

co-locating one or more sensors with one or more nodes that can detect the positional relationship to one or more features in the surroundings;

detecting one or more features in the surrounding by the co-located sensors;

using the positional relationship to the feature from multiple passes of the same node by the filtering mechanism; and

determining node position.

13. The method of claim 1, further comprising the steps of:

co-locating one or more sensors with one or more nodes that can detect the positional relationship to one or more features in the surroundings;

detecting one or more features in the surrounding by the co-located sensors;

using the positional relationship to the feature from multiple passes of multiple nodes by the filtering mechanism; and

determining node position.

14. The method of claim 1, further comprising the steps of:

providing a display screen; and

allowing each node to know its location and the location of other nodes.

15. The method of claim 14, further comprising the steps of:

generating a partial or fused map from the locations of the nodes; and

displaying the partial or fused maps on the display screen.

16. The method of claim 1, further comprising the step of:

determining the node location of other nodes that the individual node location when it has active communications between the two nodes.

17. The method of claim 16, further comprising the step of:

re-incorporating one or more nodes that come back into active communications or have data relayed through other nodes.

18. The method of claim 1, further comprising the step of:

selecting which data to use in the filter.