Detection and mapping of generalized retroreflective surfaces

Patent metadata

Field	Value
Publication number	US-12468306-B2
Application number	US-202318222387-A
Country	US
Kind code	B2
Filing date	Jul 14, 2023
Priority date	Jul 14, 2023
Publication date	Nov 11, 2025
Grant date	Nov 11, 2025

Abstract

A method comprises monitoring, by a processor, using a sensor of a first vehicle, data associated with a retroreflective feature near a road being driven by the first vehicle; vectorizing, by the processor, the data associated with the retroreflective feature; generating, by the processor, a digital map including vectorized data associated with the retroreflective feature and a location associated with the retroreflective feature; receiving, by the processor, data associated with the retroreflective feature from a second vehicle; and executing, by the processor, a localization protocol to identify a location of the second vehicle using the digital map.

First claim

What is claimed is:

1 . A method comprising:
monitoring, by a processor, using a sensor of a first vehicle, data associated with a retroreflective feature near a road being driven by the first vehicle; collecting, by the processor, using the sensor of the first vehicle, the data associated with the retroreflective feature; vectorizing, by the processor, the data associated with the retroreflective feature; generating, by the processor, a digital map including vectorized data associated with the retroreflective feature and a location associated with the retroreflective feature; receiving, by the processor, data associated with the retroreflective feature from a second vehicle; and executing, by the processor, a localization protocol to identify a location of the second vehicle using the digital map.

2 . The method of claim 1 , wherein the location of the second vehicle is identified in accordance with a position and velocity of the second vehicle with respect to the retroreflective feature.

3 . The method of claim 1 , wherein the location of the second vehicle is further identified by a location-tracking sensor of the second vehicle.

4 . The method of claim 1 , further comprising:
transmitting, by the processor, the location of the second vehicle to an autonomous driving processor associated with the second vehicle.

5 . The method of claim 1 , where the sensor of the first vehicle is a LiDAR sensor.

6 . The method of claim 5 , further comprising:
generating, by the processor, a cuboid representing the retroreflective feature.

7 . The method of claim 1 , wherein the localization protocol comprises:
simulating, by the processor, a plurality of locations for the second vehicle; and generating, by the processor, a score for each simulated location.

8 . A non-transitory machine-readable storage medium having computer-executable instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations comprising:
monitoring using a sensor of a first vehicle, data associated with a retroreflective feature near a road being driven by the first vehicle; collecting, using the sensor of the first vehicle, the data associated with the retroreflective feature; vectorizing the data associated with the retroreflective feature; generating a digital map including vectorized data associated with the retroreflective feature and a location associated with the retroreflective feature; receiving data associated with the retroreflective feature from a second vehicle; and executing, by the processor, a localization protocol to identify a location of the second vehicle using the digital map.

9 . The non-transitory machine-readable storage medium of claim 8 , wherein the location of the second vehicle is identified in accordance with a position and velocity of the second vehicle with respect to the retroreflective feature.

10 . The non-transitory machine-readable storage medium of claim 8 , wherein the location of the second vehicle is further identified by a location-tracking sensor of the second vehicle.

11 . The non-transitory machine-readable storage medium of claim 8 , wherein the instructions further cause the one or more processors to:
transmit the location of the second vehicle to an autonomous driving processor associated with the second vehicle.

12 . The non-transitory machine-readable storage medium of claim 8 , where the sensor of the first vehicle is a LiDAR sensor.

13 . The non-transitory machine-readable storage medium of claim 12 , wherein the instructions further cause the one or more processors to:
generate a cuboid representing the retroreflective feature.

14 . The method of claim 1 , wherein the localization protocol comprises:
simulating a plurality of locations for the second vehicle; and generating a score for each simulated location.

15 . A system comprising a processor configured to:
monitor using a sensor of a first vehicle, data associated with a retroreflective feature near a road being driven by the first vehicle; collect, using the sensor of the first vehicle, the data associated with the retroreflective feature; vectorize the data associated with the retroreflective feature; generate a digital map including vectorized data associated with the retroreflective feature and a location associated with the retroreflective feature; receive data associated with the retroreflective feature from a second vehicle; and execute a localization protocol to identify a location of the second vehicle using the digital map.

16 . The system of claim 15 , wherein the location of the second vehicle is identified in accordance with a position and velocity of the second vehicle with respect to the retroreflective feature.

17 . The system of claim 15 , wherein the location of the second vehicle is further identified by a location-tracking sensor of the second vehicle.

18 . The system of claim 15 , wherein the processor is further configured to:
transmit the location of the second vehicle to an autonomous driving processor associated with the second vehicle.

19 . The system of claim 15 , where the sensor of the first vehicle is a LiDAR sensor.

20 . The system of claim 15 , wherein the processor is further configured to:
generate a cuboid representing the retroreflective feature.

Assignees

• Torc Robotics Inc

Inventors

• Foster Wade
• Chilton Ryan
• Bhargava Karan Vivek
• Udayakumar Gowtham Raj Gunaseela
• Pullagurla Harish
• Harper Jason
• Miller Zachary

Classifications

• G05D1/43

  Control of position or course in two dimensions [2D] · CPC title

• G05D2111/52

  generated by inertial navigation means, e.g. gyroscopes or accelerometers · CPC title

• H04W4/027

  using movement velocity, acceleration information · CPC title

• H04W4/029 Primary

  Location-based management or tracking services · CPC title

• G05D1/027 Primary

  comprising intertial navigation means, e.g. azimuth detector (inertial navigation G01C21/16; inertial navigation combined with non-inertial navigation instruments G01C21/165) · CPC title