Brian Daniel Beyer

US Patent:

20220253063, Aug 11, 2022

Filed:

Apr 28, 2022

Appl. No.:

17/732255

Inventors:

- Bloomington MN, US
Jason Thomas Kraft - Stillwater MN, US
Ryan Douglas Ingvalson - Sewickley PA, US
David Arthur LaRose - Pittsburgh PA, US
Zachary Irvin Parker - Pittsburgh PA, US
Adam Richard Williams - Mountain View CA, US
Stephen Paul Elizondo Landers - Pittsburgh PA, US
Michael Jason Ramsay - Verona PA, US
Brian Daniel Beyer - Pittsburgh PA, US

International Classification:

G05D 1/02
G01C 21/32
G05D 1/00
A01D 34/00
A01D 34/82

Abstract:

Autonomous machine navigation techniques may generate a three-dimensional point cloud that represents at least a work region based on feature data and matching data. Pose data associated with points of the three-dimensional point cloud may be generated that represents poses of an autonomous machine. A boundary may be determined using the pose data for subsequent navigation of the autonomous machine in the work region. Non-vision-based sensor data may be used to determine a pose. The pose may be updated based on the vision-based pose data. The autonomous machine may be navigated within the boundary of the work region based on the updated pose. The three-dimensional point cloud may be generated based on data captured during a touring phase. Boundaries may be generated based on data captured during a mapping phase.

US Patent:

20200050208, Feb 13, 2020

Filed:

Aug 7, 2019

Appl. No.:

16/534515

Inventors:

- Bloomington MN, US
Jason Thomas Kraft - Stillwater MN, US
Ryan Douglas Ingvalson - Loretto MN, US
David Arthur LaRose - Pittsburgh PA, US
Zachary Irvin Parker - Pittsburgh PA, US
Adam Richard Williams - Mountain View CA, US
Stephen Paul Elizondo Landers - Pittsburgh PA, US
Michael Jason Ramsay - Verona PA, US
Brian Daniel Beyer - Pittsburgh PA, US

International Classification:

G05D 1/02
G05D 1/00
G01C 21/32

Abstract:

Autonomous machine navigation techniques may generate a three-dimensional point cloud that represents at least a work region based on feature data and matching data. Pose data associated with points of the three-dimensional point cloud may be generated that represents poses of an autonomous machine. A boundary may be determined using the pose data for subsequent navigation of the autonomous machine in the work region. Non-vision-based sensor data may be used to determine a pose. The pose may be updated based on the vision-based pose data. The autonomous machine may be navigated within the boundary of the work region based on the updated pose. The three-dimensional point cloud may be generated based on data captured during a touring phase. Boundaries may be generated based on data captured during a mapping phase.