IP Library › Granted Patent US 12,461,231
Granted Patent B2
US 12,461,231 · App. 17/584,435 · Granted Nov 4, 2025

Thermal sensor data vehicle perception

Inventors: Bence Cserna (East Boston, MA); Aravindkumar Vijayalingam (Singapore, SG); Ruben Strenzke (Singapore, SG)
Assignee: Motional AD LLC
G01S13/931B60W60/0016G01J5/00G01S17/931B60W2420/40B60W2420/403B60W2420/408B60W2420/54G01J2005/0077
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,461,231
App. No.
17/584,435
Granted
Nov 4, 2025
Kind
B2
Abstract

Provided are methods for thermal sensor data vehicle perception, which can include obtaining thermal sensor data, obtaining non-thermal sensor data, and determining, based on the thermal sensor data and the non-thermal sensor data, a perception parameter indicative of an object. Some methods described also include generating a trajectory for an autonomous vehicle. Systems and computer program products are also provided.

Claims (45)

1 . A method comprising:

obtaining, by at least one processor, thermal sensor data associated with an environment in which an autonomous vehicle is operating;

obtaining, using the at least one processor, non-thermal sensor data associated with the environment;

identifying, using the at least one processor, a thermal reflection on a surface of a first object in the environment based at least in part on the thermal sensor data;

determining, using the at least one processor, a presence of a second object based at least in part on the identified thermal reflection on the surface of the first object; and

generating, using the at least one processor, a trajectory for the autonomous vehicle based at least in part on the determined presence of the second object.

2 . The method of claim 1 , the method comprising:

determining, using the at least one processor, based at least in part on the thermal sensor data, a reaction parameter for an emergency reaction; and

generating, using the at least one processor, based at least in part on the reaction parameter, a second trajectory for the autonomous vehicle.

3 . The method of claim 1 , wherein the second object is an agent.

4 . The method of claim 1 , wherein the thermal sensor data is obtained from one or more of: a thermal camera and an infrared thermal sensor.

5 . The method of claim 1 , wherein the non-thermal sensor data is obtained from one or more of: an image sensor, a Light Detection and Ranging (LiDAR) sensor, a RADAR sensor, and an ultrasonic sensor.

6 . The method of claim 1 , wherein the identified thermal reflection on the surface of the first object is indicative of a state of the second object.

7 . The method of claim 1 , wherein the identified thermal reflection on the surface of the first object is indicative of a feature of the second object.

8 . The method of claim 7 , wherein the feature is one or more of: a light, a doorknob, a window frame, and a window.

9 . The method of claim 1 , wherein the first object comprises a driving surface.

10 . The method of claim 1 , further comprising determining, using the at least one processor, based on the thermal sensor data and the identified thermal reflection on the surface of the first object, one or more segments of the second object.

11 . The method of claim 1 , wherein generating the trajectory for the autonomous vehicle comprises prioritizing, using the at least one processor, based at least in part on the identified thermal reflection on the surface of the first object, the second object.

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

predicting, using the at least one processor, based at least in part on the identified thermal reflection on the surface of the first object, an object trajectory of the second object.

13 . The method of claim 12 , wherein predicting the object trajectory comprises:

overlaying, using the at least one processor, based at least in part on the identified thermal reflection on the surface of the first object, a representation of the thermal sensor data on a three-dimension reconstruction of the second object;

estimating, using the at least one processor, based at least in part on the identified thermal reflection on the surface of the first object, a location of the second object; and

predicting, using the at least one processor, based at least in part on the estimated location, the object trajectory of the second object.

14 . The method of claim 12 , wherein generating the trajectory for the autonomous vehicle comprises generating, using the at least one processor, based at least in part on the object trajectory, the trajectory for the autonomous vehicle.

15 . A non-transitory computer readable medium comprising instructions stored thereon that, when executed by at least one processor, cause the at least one processor to carry out operations comprising:

obtaining, by at least one processor, thermal sensor data associated with an environment in which an autonomous vehicle is operating;

obtaining, using the at least one processor, non-thermal sensor data associated with the environment;

identifying, using the at least one processor, a thermal reflection on a surface of a first object in the environment based at least in part on the thermal sensor data;

determining, using the at least one processor, a presence of a second object based at least in part on the identified thermal reflection on the surface of the first object; and

generating, using the at least one processor, a trajectory for the autonomous vehicle based at least in part on the determined presence of the second object.

16 . A system, comprising at least one processor; and at least one memory storing instructions thereon that, when executed by the at least one processor, cause the at least one processor to:

obtain thermal sensor data associated with an environment in which an autonomous vehicle is operating;

obtain non-thermal sensor data associated with the environment;

identify a thermal reflection on a surface of a first object in the environment based at least in part on the thermal sensor data;

determine, using the at least one processor, a presence of a second object based at least in part on the identified thermal reflection on the surface of the first object; and

generate a trajectory for the autonomous vehicle based at least in part on the determined presence of the second object.

17 . The system of claim 16 , wherein the at least one memory storing instructions, when executed by at least one processor, cause the at least one processor to:

predict, based at least in part on the identified thermal reflection on the surface of the first object, an object trajectory of the second object.

18 . The system of claim 17 , wherein to predict the object trajectory comprises to:

overlay, based at least in part on the identified thermal reflection on the surface of the first object, a representation of the thermal reflection on a three-dimension reconstruction of the second object;

estimate, based at least in part on the identified thermal reflection on the surface of the first object, a location of the second object; and

predict, based at least in part on the estimated location, the object trajectory of the second object.

19 . The method of claim 1 , wherein the second object is occluded from the non-thermal sensor data.

20 . The method of claim 1 , wherein the second object is occluded from the autonomous vehicle.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 24, 2022
From: CSERNA, BENCE; VIJAYALINGAM, ARAVINDKUMAR; STRENZKE, RUBEN
To: MOTIONAL AD LLC
Reel/Frame 059084/0320 →
Continuity (1)
Related Publication 20230236313A1 · Jul 27, 2023
References Cited (55)
US 5377116A · Wayne et al. · 1994 [cited by applicant]
US 5999212A · Crosby · 1999 [cited by examiner]
US 6151539A · Bergholz et al. · 2000 [cited by applicant]
US 6799087B2 · Estkowski · 2004 [cited by applicant]
US 9575007B2 · Rao · 2017 [cited by examiner]
US 9813643B2 · Terre · 2017 [cited by examiner]
US 9921584B2 · Rao · 2018 [cited by examiner]
US 10732260B2 · Ajanoh · 2020 [cited by examiner]
US 10809910B2 · Iglesias · 2020 [cited by examiner]
US 10819923B1 · McCauley · 2020 [cited by examiner]
US 11010622B2 · Naser · 2021 [cited by examiner]
US 11192734B2 · Kibler et al. · 2021 [cited by applicant]
US 11226634B2 · Rao · 2022 [cited by examiner]
US 11284022B2 · Zhang · 2022 [cited by examiner]
US 11735099B1 · Wo · 2023 [cited by examiner]
US 11741716B2 · Radu · 2023 [cited by examiner]
US 11780471B1 · Beilouni · 2023 [cited by examiner]
US 11906657B2 · Preece · 2024 [cited by examiner]
US 12063059B2 · Russell · 2024 [cited by examiner]
US 12200572B2 · Russell · 2025 [cited by examiner]
US 20040088079A1 · Lavarec · 2004 [cited by examiner]
US 20150358557A1 · Terre · 2015 [cited by examiner]
US 20160202199A1 · Rao · 2016 [cited by examiner]
US 20170160746A1 · Rao · 2017 [cited by examiner]
US 20180120842A1 · Smith et al. · 2018 [cited by applicant]
US 20180120852A1 · Cho · 2018 [cited by examiner]
US 20180203459A1 · Rao · 2018 [cited by examiner]
US 20190064815A1 · Haynes · 2019 [cited by applicant]
US 20190072645A1 · Ajanoh · 2019 [cited by examiner]
US 20190146511A1 · Hurd et al. · 2019 [cited by applicant]
US 20190294897A1 · Cohen et al. · 2019 [cited by applicant]
US 20200103499A1 · Preece · 2020 [cited by examiner]
US 20200104025A1 · Iglesias · 2020 [cited by examiner]
US 20200133295A1 · Indrakanti et al. · 2020 [cited by applicant]
US 20200143179A1 · Naser · 2020 [cited by examiner]
US 20200310753A1 · Radu · 2020 [cited by examiner]
US 20200326720A1 · Rao · 2020 [cited by examiner]
US 20210152754A1 · McCauley · 2021 [cited by examiner]
US 20210218814A1 · Tran · 2021 [cited by applicant]
US 20220046194A1 · Zhang · 2022 [cited by examiner]
US 20220185266A1 · Shah · 2022 [cited by applicant]
US 20220214222A1 · Tauber · 2022 [cited by examiner]
US 20220291701A1 · Posch · 2022 [cited by examiner]
US 20230217215A1 · Russell · 2023 [cited by examiner]
US 20230231591A1 · Russell · 2023 [cited by examiner]
US 20240104765A1 · Babazaki · 2024 [cited by examiner]
CN 111409631 · 2020 [cited by applicant]
CN 112406860A · 2021 [cited by applicant]
CN 113837217A · 2021 [cited by examiner]
SE 1950963A1 · 2021 [cited by applicant]
SAE On-Road Automated Vehicle Standards Committee, “SAE International's Standard J3016: Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles”, Jun. 2018, in 35 pages. [cited by applicant]
Great Britain Office Action issued for Application No. GB 2201963.2, dated Jul. 25, 2022. [cited by applicant]
Korean Office Action issued for Application No. KR 10-2022-0038904, dated Jan. 23, 2024. [cited by applicant]
Korean Office Action issued for Application No. KR 10-2022-0038904, dated Jul. 26, 2024. [cited by applicant]
Korean Office Action issued for Application No. KR 10-2022-0038904, dated Feb. 27, 2025. [cited by applicant]