MOBILE LOCALIZATION USING SPARSE TIME-OF-FLIGHT RANGES AND DEAD RECKONING

• US 20160349362A1
• Filed: 06/01/2016
• Published: 12/01/2016
• Est. Priority Date: 05/08/2015
• Status: Active Grant

• Current Assignee: Humatics Corporation
• Original Assignee: 5D Robotics, Inc. (Humatics Corporation)
• Inventors: Rohr, David, Senna, Josh, Jain, Akshay Kumar, Atherton, J Alan, Bruemmer, David J.
• Granted Patent: US 10,365,363 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G01C 21/12 executed aboard the object being navigated; Dead reckoning
• CPC Class Codes: G01C 21/28 with correlation of data from several navigational instruments
• CPC Class Codes: G01S 13/0209 Systems with very large relative bandwidth, i.e. larger than 10 %, e.g. baseband, pulse, carrier-free, ultrawideband
• CPC Class Codes: G01S 13/06 Systems determining position data of a target
• CPC Class Codes: G01S 13/86 Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
• CPC Class Codes: G01S 17/06 Systems determining position data of a target
• CPC Class Codes: G01S 17/42 Simultaneous measurement of distance and other co-ordinates indirect measurement G01S17/46
• CPC Class Codes: G01S 17/86 Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
• CPC Class Codes: G01S 19/26 involving a sensor measurement for aiding acquisition or tracking
• CPC Class Codes: G01S 5/0264 at least one of the systems being a non-radio wave positioning system

Abstract

Mobile localization of an object having an object positional frame of reference using sparse time-of-flight data and dead reckoning can be accomplished by creating a dead reckoning local frame of reference, including an estimation of object position with respect to known locations from one or more Ultra Wide Band transceivers. As the object moves along its path, a determination is made using the dead-reckoning local frame of reference. When the object is within a predetermine range of one or more of the Ultra Wide Band transceivers, a “conversation” is initiated, and range data between the object and the UWB transceiver(s) is collected. Using multiple conversations to establish accurate range and bearing information, the system updates the object'"'"'s position based on the collected data.

Claims

1. A system for mobile localization of an object having an object positional frame of reference using sparse time-of-flight data and dead reckoning, the system comprising:

one or more transmitters;

a dead reckoning module wherein the dead reckoning module creates a dead reckoning local frame of reference;

a time-of-flight module wherein, responsive to the object being within range of one of the one or more transmitters based on the dead reckoning local frame of reference, the time-of-flight module receives a signal from the transmitter and collects range data between the object and the transmitter; and

a localization module communicatively coupled to the dead reckoning module and the time-of-flight module, wherein the localization module updates the object positional frame of reference based on the collected range data.

2. The system for mobile localization of an object using sparse time-of-flight data and dead reckoning according to claim 1, wherein each transmitter includes a unique identifier.

3. The system for mobile localization of an object using sparse time-of-flight data and dead reckoning according to claim 1, responsive to the object being within a threshold distance of a predefined transmitter location, initiating an exchange of signals with the transmitter.

4. The system for mobile localization of an object using sparse time-of-flight data and dead reckoning according to claim 3, wherein the exchange of signals includes a time stamp associated with the conversation and paired with the dead reckoning local frame of reference position.

5. The system for mobile localization of an object using sparse time-of-flight data and dead reckoning according to claim 1, wherein the localization module performs a “

best-fit”

optimization path based on range data, the predefined transmitter location and the time stamp

6. The system for mobile localization of an object using sparse time-of-flight data and dead reckoning according to claim 5, wherein the best fit optimization is a “

least-squares”

optimization.

7. The system for mobile localization of an object using sparse time-of-flight data and dead reckoning according to claim 1, wherein responsive to conducting a plurality of signal exchanges between the transmitter and the object, performing a non-linear, “

least-squares”

optimization to update the object positional frame of reference.

8. A method for mobile localization of an object having an object positional frame of reference using sparse time-of-flight data and dead reckoning, the method comprising the steps:

creating a dead reckoning local frame of reference wherein the dead reckoning local frame of reference includes an estimation of localization of the object with respect to known locations of one or more Ultra Wide Band (UWB) transceivers;

determining when the estimation of localization of the object is within a predetermine range of one or more of the Ultra Wide Band transceivers;

initiating a conversation with one of the one or more of the UWB transceivers within the predetermined range;

receiving a signal from the one of the one or more UWB transceivers within the predetermined range;

collecting range data between the object and the one of the one or more UWB transceivers within the predetermined range; and

updating the object positional frame of reference based on the collected range data.

9. The method for mobile localization of an object according to claim 8, wherein each UWB includes a unique identifier.

10. The method for mobile localization of an object according to claim 8, wherein the signal includes a time stamp associated with the conversation and paired with the dead reckoning local frame of reference.

11. The method for mobile localization of an object according to claim 10, wherein updating includes performing a “

best-fit”

optimization path based on collected range data, known locations of the one or more Ultra Wide Band (UWB) transceivers and the time stamp.

12. The method for mobile localization of an object according to claim 11, wherein the “

best-fit”

optimization is a “

least-squares”

optimization.

13. The method for mobile localization of an object according to claim 8, wherein updating includes performing a non-linear, “

least-squares”

optimization to update the object positional frame of reference.