# US 2021/0333373 A1 · Eliminating sensor self-hit data

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- Number: US 2021/0333373 A1
- Document ID: US20210333373A1
- Status: Published application
- Kind: A1
- Application number: 16/855,478
- Filed: 2020-04-22
- Published: 2021-10-28
- Earliest claimed: 2020-04-22
- Assignees: GM Cruise Holdings LLC
- Applicants: GM Cruise Holdings LLC
- Inventors: Sandeep Gangundi; Avinash Nair; Abdelrahman Elogeel; Kyle Vogt; Cornelis Jacob Lekkerkerker
- Web page: https://patentgrep.com/patent/US20210333373A1

## CPC

- G01S 7/4876: {by removing unwanted signals (G01S7/495 takes precedence)}
- G01S 17/89: for mapping or imaging
- G01S 7/4802: {using analysis of echo signal for target characterisation; Target signature; Target cross-section}
- G01S 7/493: Extracting wanted echo signals
- G01S 17/931: of land vehicles
- G06F 30/15: Vehicle, aircraft or watercraft design
- G01S: RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

The subject disclosure relates to ways to identify self-hit data collected by autonomous vehicle (AV) sensors. In some aspects, a method of the disclosed technology includes steps for generating a geometric model of an autonomous vehicle (AV), wherein the geometric model specifies physical boundaries of the AV in three-dimensional (3D) space, collecting sensor data for an environment around the AV, and identifying one or more data points, from among the collected sensor data, that correspond with a surface of the AV. Systems and machine-readable media are also provided.

## Claims

### Claim 1

A computer-implemented method, comprising:
generating a geometric model of an autonomous vehicle (AV), wherein the geometric model specifies physical boundaries of the AV in three-dimensional (3D) space;
collecting sensor data for an environment around the AV; and
identifying one or more data points, from among the collected sensor data, that correspond with a surface of the AV.

### Claim 2 (depends on 1)

The computer-implemented method of claim 1, further comprising:
identifying the one or more data points from among the collected sensor data as self-hit data points.

### Claim 3 (depends on 1)

The computer-implemented method of claim 1, further comprising:
collecting Light Detection and Ranging (LiDAR) test data for an environment around the AV;
generating a filter mask based on the geometric model and the LiDAR test data, and
wherein identifying the one or more data points that correspond with the surface of the AV is based on the filter mask.

### Claim 4 (depends on 1)

The computer-implemented method of claim 1, wherein the geometric model is a Computer-aided Design (CAD) model of the AV.

### Claim 5 (depends on 1)

The computer-implemented method of claim 1, wherein the sensor data comprises Light Detection and Ranging (LiDAR) data.

### Claim 6 (depends on 1)

The computer-implemented method of claim 1, further comprising:
collecting test data for an environment around the AV, and wherein the geometric model of the AV is based on the test data.

### Claim 7 (depends on 1)

The computer-implemented method of claim 1, wherein the geometric model comprises one or more buffers to facilitate use of the model on different vehicle types.

### Claim 8

A system for detecting sensor data self-hits, the system comprising:
one or more processors;
at least one Light Detection and Ranging (LiDAR) sensor coupled to the one or more processors; and
a computer-readable medium comprising instructions stored therein, which when executed by the processors, cause the processors to perform operations comprising:
generating a geometric model of an autonomous vehicle (AV), wherein the geometric model specifies physical boundaries of the AV in three-dimensional (3D) space;
collecting sensor data for an environment around the AV; and
identifying one or more data points, from among the collected sensor data, that correspond with a surface of the AV.

### Claim 9 (depends on 8)

The system of claim 8, wherein the one or more processors are further configured to perform operations comprising:
identifying the one or more data points from among the collected sensor data as self-hit data points.

### Claim 10 (depends on 8)

The system of claim 8, wherein the one or more processors are further configured to perform operations comprising:
collecting Light Detection and Ranging (LiDAR) test data for an environment around the AV;
generating a filter mask based on the geometric model and the LiDAR test data, and
wherein identifying the one or more data points that correspond with the surface of the AV is based on the filter mask.

### Claim 11 (depends on 8)

The system of claim 8, wherein the geometric model is a Computer-aided Design (CAD) model of the AV.

### Claim 12 (depends on 8)

The system of claim 8, wherein the sensor data comprises Light Detection and Ranging (LiDAR) data.

### Claim 13 (depends on 8)

The system of claim 8, wherein the one or more processors are further configured to perform operations comprising:
collecting test data for an environment around the AV, and wherein the geometric model of the AV is based on the test data.

### Claim 14 (depends on 8)

The system of claim 8, wherein the geometric model comprises one or more buffers to facilitate use of the model on different vehicle types.

### Claim 15

A non-transitory computer-readable storage medium comprising instructions stored therein, which when executed by one or more processors, cause the processors to perform operations comprising:
generating a geometric model of an autonomous vehicle (AV), wherein the geometric model specifies physical boundaries of the AV in three-dimensional (3D) space;
collecting sensor data for an environment around the AV; and
identifying one or more data points, from among the collected sensor data, that correspond with a surface of the AV.

### Claim 16 (depends on 15)

The non-transitory computer-readable storage medium of claim 15, wherein the one or more processors are further configured to perform operations comprising:
identifying the one or more data points from among the collected sensor data as self-hit data points.

### Claim 17 (depends on 15)

The non-transitory computer-readable storage medium of claim 15, wherein the one or more processors are further configured to perform operations comprising:
collecting Light Detection and Ranging (LiDAR) test data for an environment around the AV;
generating a filter mask based on the geometric model and the LiDAR test data, and
wherein identifying the one or more data points that correspond with the surface of the AV is based on the filter mask.

### Claim 18 (depends on 15)

The non-transitory computer-readable storage medium of claim 15, wherein the geometric model is a Computer-aided Design (CAD) model of the AV.

### Claim 19 (depends on 15)

The non-transitory computer-readable storage medium of claim 15, wherein the sensor data comprises Light Detection and Ranging (LiDAR) data.

### Claim 20 (depends on 15)

The non-transitory computer-readable storage medium of claim 15, wherein the one or more processors are further configured to perform operations comprising:
collecting test data for an environment around the AV, and wherein the geometric model of the AV is based on the test data.