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公开(公告)号:US12216468B2
公开(公告)日:2025-02-04
申请号:US18085901
申请日:2022-12-21
Applicant: Built Robotics Inc.
Abstract: An autonomous off-road vehicle (AOV) autonomously performs a pile driving operation by driving a pile into the ground at a location identified by a pile plan map. The AOV detects one or more attributes of the pile using one or more sensors during or after the pile driving operation. The AOV determines whether the one or more attributes of the pile exceed respective tolerance thresholds. The AOV performs a quality control action in response to determining that the one or more attributes of the pile exceed the respective tolerance thresholds. The one or more attributes include one or more of a location and an orientation of the pile, and the quality control action is performed in response to determining that the location or the orientation of the pile exceeds the respective tolerance threshold.
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公开(公告)号:US12098528B2
公开(公告)日:2024-09-24
申请号:US18315791
申请日:2023-05-11
Applicant: Built Robotics Inc.
CPC classification number: E02F9/265 , E02F9/262 , G05D1/0061 , G06N3/08
Abstract: In some implementations, the EMV uses a calibration to inform autonomous control over the EMV. To calibrate an EMV, the system first selects a calibration action comprising a control signal for actuating a control surface of the EMV. Then, using a calibration model comprising a machine learning model trained based on one or more previous calibration actions taken by the EMV, the system predicts a response of the control surface to the control signal of the calibration action. After the EMV executes the control signal to perform the calibration action, the EMV system monitors the actual response of the control signal and uses that to update the calibration model based on a comparison between the predicted and monitored states of the control surface.
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公开(公告)号:US12066825B2
公开(公告)日:2024-08-20
申请号:US18325418
申请日:2023-05-30
Applicant: Built Robotics Inc.
CPC classification number: G05D1/0088 , G05D1/0212 , G06N20/00
Abstract: An autonomous earth moving system can determine a desired state for a portion of the EMV including at least one control surface. Then the EMV selects a set of control signals for moving the portion of the EMV from the current state to the desired state using a machine learning model trained to generate control signals for moving the portion of the EMV to the desired state based on the current state. After the EMV executes the selected set of control signals, the system measures an updated state of the portion of the EMV. In some cases, this updated state of the EMV is used to iteratively update the machine learning model using an online learning process.
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公开(公告)号:US20240210947A1
公开(公告)日:2024-06-27
申请号:US18483652
申请日:2023-10-10
Applicant: Built Robotics Inc.
IPC: G05D1/02
CPC classification number: G05D1/0274 , G05D2201/0202
Abstract: An autonomous off-road vehicle (AOV) accesses a pile plan map indicating a plurality of locations within a geographic area at which piles are to be installed. The AOV generates an obstacle map indicating locations of obstacles within the geographic area. The AOV autonomously navigates to a first location of the plurality of locations using the pile plan map. In response to driving a pile into the ground at the first location, the AOV modifies the obstacle map to include a representation of the pile at the first location. The AOV autonomously navigates to a second location of the plurality of locations using the pile plan map. In response to driving a pile into ground at the second location, the AOV modifies the obstacle map that includes the representation of the pile at the first location to further include a representation of the pile at the second location.
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公开(公告)号:US20230305560A1
公开(公告)日:2023-09-28
申请号:US18325418
申请日:2023-05-30
Applicant: Built Robotics Inc.
CPC classification number: G05D1/0088 , G05D1/0212 , G06N20/00 , G05D2201/0202
Abstract: An autonomous earth moving system can determine a desired state for a portion of the EMV including at least one control surface. Then the EMV selects a set of control signals for moving the portion of the EMV from the current state to the desired state using a machine learning model trained to generate control signals for moving the portion of the EMV to the desired state based on the current state. After the EMV executes the selected set of control signals, the system measures an updated state of the portion of the EMV. In some cases, this updated state of the EMV is used to iteratively update the machine learning model using an online learning process.
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公开(公告)号:US11732437B2
公开(公告)日:2023-08-22
申请号:US17875233
申请日:2022-07-27
Applicant: Built Robotics Inc.
Inventor: Noah Austen Ready-Campbell , Andrew Xiao Liang , Linus Page Chou , Edward Stephen Walker , Christian John Wawrzonek , Cyrus McMann Ready-Campbell
IPC: E02F3/43 , E02F9/26 , E02F3/32 , E02F3/96 , G06T7/73 , G01C21/20 , G01N33/24 , G05D1/00 , G05D1/02 , G06T17/05 , G06V20/56 , E02F9/20
CPC classification number: E02F3/435 , E02F3/32 , E02F3/434 , E02F3/439 , E02F3/964 , E02F9/205 , E02F9/2029 , E02F9/262 , E02F9/265 , G01C21/20 , G01N33/24 , G05D1/0088 , G05D1/0219 , G05D1/0231 , G05D1/0274 , G06T7/74 , G06T17/05 , G06V20/56 , G05D2201/0202 , G06T2207/30248
Abstract: This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collects any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.
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公开(公告)号:US20220412057A1
公开(公告)日:2022-12-29
申请号:US17748999
申请日:2022-05-19
Applicant: Built Robotics Inc.
Abstract: In some implementations, the EMV uses a calibration to inform autonomous control over the EMV. To calibrate an EMV, the system first selects a calibration action comprising a control signal for actuating a control surface of the EMV. Then, using a calibration model comprising a machine learning model trained based on one or more previous calibration actions taken by the EMV, the system predicts a response of the control surface to the control signal of the calibration action. After the EMV executes the control signal to perform the calibration action, the EMV system monitors the actual response of the control signal and uses that to update the calibration model based on a comparison between the predicted and monitored states of the control surface.
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公开(公告)号:US20220364321A1
公开(公告)日:2022-11-17
申请号:US17875233
申请日:2022-07-27
Applicant: Built Robotics Inc.
Inventor: Noah Austen Ready-Campbell , Andrew Xiao Liang , Linus Page Chou , Edward Stephen Walker , Christian John Wawrzonek , Cyrus McMann Ready-Campbell
IPC: E02F3/43 , E02F9/26 , E02F3/32 , E02F3/96 , G06T7/73 , G01C21/20 , G01N33/24 , G05D1/00 , G05D1/02 , G06T17/05 , G06V20/56 , E02F9/20
Abstract: This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collects any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.
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公开(公告)号:US11237558B1
公开(公告)日:2022-02-01
申请号:US17359425
申请日:2021-06-25
Applicant: Built Robotics Inc.
IPC: E01C19/00 , E01C21/00 , E01C23/00 , E02F3/00 , E02F5/00 , E21C49/02 , G05D1/00 , G06N20/00 , G05D1/02
Abstract: An autonomous earth moving system can determine a desired state for a portion of the EMV including at least one control surface. Then the EMV selects a set of control signals for moving the portion of the EMV from the current state to the desired state using a machine learning model trained to generate control signals for moving the portion of the EMV to the desired state based on the current state. After the EMV executes the selected set of control signals, the system measures an updated state of the portion of the EMV. In some cases, this updated state of the EMV is used to iteratively update the machine learning model using an online learning process.
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公开(公告)号:US11072906B2
公开(公告)日:2021-07-27
申请号:US16673937
申请日:2019-11-04
Applicant: Built Robotics Inc.
Inventor: Noah Austen Ready-Campbell , Andrew Xiao Liang , Linus Page Chou , Edward Stephen Walker, Jr. , Christian John Wawrzonek , Cyrus McMann Ready-Campbell
Abstract: This description provides an autonomous or semi-autonomous excavation vehicle that is capable of navigating through a dig site and carrying out an excavation routine using a system of sensors physically mounted to the excavation vehicle. The sensors collect any one or more of spatial, imaging, measurement, and location data representing the status of the excavation vehicle and its surrounding environment. Based on the collected data, the excavation vehicle executes instructions to carry out an excavation routine. The excavation vehicle is also able to carry out numerous other tasks, such as checking the volume of excavated earth in an excavation tool, and helping prepare a digital terrain model of the site as part of a process for creating the excavation routine.
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