IP Library Patent Application 17307477
Patent Application
App. No. 17/307,477

Mapping System and Method

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Quick Facts
Patent No.
US None
App. No.
17/307,477
Abstract

A method, computer program product, and computing system for receiving metric data that is based, at least in part, upon sensor data generated by various sensors of an autonomous vehicle; and processing the metric data to generate a semantic understanding of the autonomous vehicle.

Claims (54)

1 . A computer-implement method, executed on a computing device, comprising:

receiving metric data that is based, at least in part, upon sensor data generated by various sensors of an autonomous vehicle; and

processing the metric data to generate a semantic understanding of the autonomous vehicle.

2 . The computer-implement method of claim 1 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

generating a spatial understanding with respect to the autonomous vehicle.

3 . The computer-implement method of claim 1 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

generating a temporal understanding with respect to the autonomous vehicle.

4 . The computer-implement method of claim 1 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

creating/updating a semantic understanding of the autonomous vehicle and the state of the surroundings of the autonomous vehicle. thus generating a semantic view.

5 . The computer-implement method of claim 4 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle further includes:

processing the semantic understanding to make complex inferences relating to dynamic agents and static infrastructure in the environment, thus generating semantic inferences.

6 . The computer-implement method of claim 5 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle further includes:

processing the semantic understanding and the semantic inferences to make complex behavioral decisions to fulfill the navigational objectives of the autonomous vehicle.

7 . The computer-implement method of claim 4 wherein the semantic view includes one or more of:

a static infrastructure semantic view having a set of nodes that includes all static infrastructure elements; and

a dynamic agent semantic view having a set of nodes that includes:

all nodes of the static infrastructure semantic view, and

nodes for all dynamic agents.

8 . A computer program product residing on a computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising:

receiving metric data that is based, at least in part, upon sensor data generated by various sensors of an autonomous vehicle; and

processing the metric data to generate a semantic understanding of the autonomous vehicle.

9 . The computer program product of claim 8 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

generating a spatial understanding with respect to the autonomous vehicle.

10 . The computer program product of claim 8 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

generating a temporal understanding with respect to the autonomous vehicle.

11 . The computer program product of claim 8 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

creating/updating a semantic understanding of the autonomous vehicle and the state of the surroundings of the autonomous vehicle. thus generating a semantic view.

12 . The computer program product of claim 11 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle further includes:

processing the semantic understanding to make complex inferences relating to dynamic agents and static infrastructure in the environment, thus generating semantic inferences.

13 . The computer program product of claim 12 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle further includes:

processing the semantic understanding and the semantic inferences to make complex behavioral decisions to fulfill the navigational objectives of the autonomous vehicle.

14 . The computer program product of claim 11 wherein the semantic view includes one or more of:

a static infrastructure semantic view having a set of nodes that includes all static infrastructure elements; and

a dynamic agent semantic view having a set of nodes that includes:

all nodes of the static infrastructure semantic view, and

nodes for all dynamic agents.

15 . A computing system including a processor and memory configured to perform operations comprising:

receiving metric data that is based, at least in part, upon sensor data generated by various sensors of an autonomous vehicle; and

processing the metric data to generate a semantic understanding of the autonomous vehicle.

16 . The computing system of claim 15 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

generating a spatial understanding with respect to the autonomous vehicle.

17 . The computing system of claim 15 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

generating a temporal understanding with respect to the autonomous vehicle.

18 . The computing system of claim 15 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle includes:

creating/updating a semantic understanding of the autonomous vehicle and the state of the surroundings of the autonomous vehicle. thus generating a semantic view.

19 . The computing system of claim 18 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle further includes:

processing the semantic understanding to make complex inferences relating to dynamic agents and static infrastructure in the environment, thus generating semantic inferences.

20 . The computing system of claim 19 wherein processing the metric data to generate a semantic understanding of the autonomous vehicle further includes:

processing the semantic understanding and the semantic inferences to make complex behavioral decisions to fulfill the navigational objectives of the autonomous vehicle.

21 . The computing system of claim 18 wherein the semantic view includes one or more of:

a static infrastructure semantic view having a set of nodes that includes all static infrastructure elements; and

a dynamic agent semantic view having a set of nodes that includes:

all nodes of the static infrastructure semantic view, and

nodes for all dynamic agents.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 24, 2022
From: OPTIMUS RIDE INC.
To: MAGNA ELECTRONICS INC.
Reel/Frame 059088/0385 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 15, 2022
From: KARAMAN, SERTAC; HUANG, ALBERT
To: OPTIMUS RIDE, INC.
Reel/Frame 059020/0343 →