IP Library Granted Patent US 11,561,553
Granted Patent B1
US 11,561,553 · App. 16/871,898 · Granted Jan 24, 2023

System and method of providing a multi-modal localization for an object

Inventors: Zachary Dydek (Waltham, MA); Daniel Theobald (Somerville, MA)
Assignee: Vecna Robotics, Inc.
G05D1/0274G01S17/86G01S17/89G05D1/024G05D2201/0203
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Quick Facts
Patent No.
US 11,561,553
App. No.
16/871,898
Granted
Jan 24, 2023
Kind
B1
Abstract

An example method includes gathering, via a first module of a first type, first simultaneous localization and mapping data and gathering, via a second module of a second type, second simultaneous localization and mapping data. The method includes generating, via a simultaneous localization and mapping module, a first map based on the first simultaneous localization and mapping data and the second simultaneous localization and mapping data, the first map being of a first map type and generating, via the simultaneous localization and mapping module, a second map based on the first simultaneous localization and mapping data and the second simultaneous localization and mapping data, the second map being of a second map type. The map of the first type is used by vehicles with module(s) of the first and/or second types and the map of the second type is used by vehicles with a module of the second type exclusively.

Claims (34)

1. A method comprising:

gathering, via a first module of a first type configured on a mobile device, first data, wherein the mobile device comprises one of a mobile robot, a vehicle, a drone, or a flying vehicle;

gathering, via a second module of a second type configured on the mobile device, second data;

generating, via a simultaneous localization and mapping module, a first map based on the first data and the second data, the first map being of a first map type; and

generating, via the simultaneous localization and mapping module, a second map based on the first data and the second data, the second map being of a second map type, wherein the first map type differs from the second map type.

2. The method of claim 1 , wherein for subsequent localization, the first map is used for a system configured with either the first module of the first type or a system configured with both the first module of the first type and the second module of the second type.

3. The method of claim 1 , wherein for subsequent localization, the second map is used for a system configured with only the second module of the second type.

4. The method of claim 1 , wherein the first module of the first type comprises a high cost module and the second module of the second type comprises a low cost module.

5. The method of claim 1 , wherein the first module of the first type comprises a high accuracy module and the second module of the second type comprises a low accuracy module.

6. The method of claim 1 , wherein the first module of the first type uses one or more of a two-dimensional LiDAR, a three-dimensional LiDAR, a Ultra Wide Band radio, radar, and a wheel odometry system.

7. The method of claim 1 , wherein the second module of the second type uses one or more of an inertial measuring unit, a camera, a WiFi sensor, a Bluetooth sensor, a global positioning system and a magnetometer.

8. The method of claim 1 , wherein a first characteristic of the first map relates to a first sensor associated with the first module of the first type.

9. The method of claim 8 , wherein a second characteristic of the second map relates to a second sensor associated with the second module of the second type.

10. A system comprising:

a processor;

a first module of a first type configured on the system, wherein the system comprises one of a mobile robot, a drone, a flying vehicle or a vehicle;

a second module of a second type configured on the system;

a simultaneous localization and mapping module configured on the system; and

a computer-readable storage device storing instructions which, when executed by the processor, cause the processor to perform operations comprising:

gathering, via the first module, first data;

gathering, via the second module, second data;

generating, via the simultaneous localization and mapping module, a first map based on the first data and the second data, the first map being of a first map type; and

generating, via the simultaneous localization and mapping module, a second map based on the first data and the second data, the second map being of a second map type, wherein the first map type differs from the second map type.

11. The system of claim 10 , wherein for subsequent localization, the first map is used for a system configured with either the first module of the first type or a system configured with both the first module of the first type and the second module of the second type and wherein, for the subsequent localization, the second map is used for a second system configured with only the second module of the second type.

12. The system of claim 10 , wherein the first module of the first type comprises a high accuracy module and the second module of the second type comprises a low accuracy module.

13. The system of claim 10 , wherein the first module of the first type uses one or more of a two-dimensional LiDAR, a three-dimensional LiDAR, a Ultra Wide Band radio, and a wheel odometry system and wherein the second module of the second type uses one or more of a inertial measuring unit, a camera, a WiFi sensor, a Bluetooth sensor, a global positioning system and a magnetometer.

14. The system of claim 10 , wherein a first characteristic of the first map relates to a first sensor associated with the first module of the first type.

15. The system of claim 14 , wherein a second characteristic of the second map relates to a second sensor associated with the second module of the second type.

16. The system of claim 10 , wherein the first module of the first type comprises a high cost module and the second module of the second type comprises a low cost module.

17. The system of claim 10 , wherein the first module of the first type comprises a high accuracy module and the second module of the second type comprises a low accuracy module.

18. The system of claim 10 , wherein the first module of the first type uses one or more of a two-dimensional LiDAR, a three-dimensional LiDAR, a Ultra Wide Band radio, radar, and a wheel odometry system.

19. The system of claim 10 , wherein the second module of the second type uses one or more of an inertial measuring unit, a camera, a WiFi sensor, a Bluetooth sensor, a global positioning system and a magnetometer.

20. The system of claim 10 , wherein a first characteristic of the first map relates to a first sensor associated with the first module of the first type.

21. The system of claim 20 , wherein a second characteristic of the second map relates to a second sensor associated with the second module of the second type.

Assignments (5)
RELEASE OF SECURITY INTEREST Recorded May 7, 2025
From: TRIPLEPOINT CAPITAL LLC
To: VECNA ROBOTICS, INC.
Reel/Frame 071220/0483 →
SECURITY INTEREST Recorded May 20, 2024
From: VECNA ROBOTICS, INC.; VECNA ROBOTICS INTERCO LLC
To: STIFEL BANK
Reel/Frame 067472/0120 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 4, 2024
From: VECNA TECHNOLOGIES, INC.
To: VECNA ROBOTICS, INC.
Reel/Frame 067020/0397 →
SECURITY AGREEMENT Recorded Dec 19, 2022
From: VECNA ROBOTICS, INC.
To: TRIPLEPOINT CAPITAL LLC, AS COLLATERAL AGENT
Reel/Frame 062156/0617 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 10, 2022
From: DYDEK, ZACHARY; THEOBALD, DANIEL
To: VECNA ROBOTICS, INC.
Reel/Frame 060767/0498 →
Cited By (4)
US 12,228,410 US 12,375,791 US 12,397,938 US 12,475,581