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公开(公告)号：US20240178565A1
公开(公告)日：2024-05-30
申请号：US18515023
申请日：2023-11-20
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
Abstract: An antenna system comprises a first plate and a second plate. The second plate is positioned below the first plate and separated by a gap from the first plate. The second plate is operatively configured to substantially block radio frequency (RF) transmissions.
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公开(公告)号：US12026235B2
公开(公告)日：2024-07-02
申请号：US17338885
申请日：2021-06-04
Applicant: MORPHIX, INC.
Inventor： Jonathan Lovegrove
CPC classification number: G06F18/2431 , F41G1/38 , G06F18/2178 , G06T7/11 , G06T7/70 , G06V20/20
Abstract: Examples are disclosed that relate to target classification systems, weapons, and methods for classifying a target. One example provides a target classification system comprising a user device, a user input device, a pose sensor fixed to the user device, a processor, and a memory storing instructions executable by the processor. A visual alignment aid indicates a line of sight to one or more of a plurality of targets. The user input device is configured to receive at least a first input type and a second input type. The instructions are executable to receive a user input and determine the pose of the line of sight. The one or more targets are tagged with a first target classification when the first input type is received and tagged with a second target classification when the second input type is received. The instructions are further executable to output targeting data to another device.
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公开(公告)号：US20230083636A1
公开(公告)日：2023-03-16
申请号：US17473858
申请日：2021-09-13
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
Abstract: Examples are disclosed that relate to methods and systems for classifying the possession or control of a target asset. One example provides a system comprising one or more computing devices having processors and associated memories storing instructions executable by the processors. The instructions are executable to conduct a simulation or observation of an in-field event comprising a plurality of actors controlling a plurality of in-field assets. The system is further configured to monitor telemetry data from each of the in-field assets. In addition, tagging data is received from an in-field asset under the control of a member of the friendly group. A training data set is generated including the telemetry data and the tagging data, and an artificial intelligence model is trained to predict whether a run-time target asset is in the possession or control of the friendly or the unfriendly actor, or lost, based on run-time telemetry data.
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公开(公告)号：US20220413458A1
公开(公告)日：2022-12-29
申请号：US17929480
申请日：2022-09-02
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
IPC: G05B19/04 , G06N20/00 , G05B19/042
Abstract: A computing device, including a processor configured to receive sensor data from a control device. The control device may include a control processor configured to execute control instructions to control an actuator of a target electromechanical system and may further include one or more sensors. The processor may identify a first subset of the sensor data and a second subset of the sensor data. The processor may generate first control instructions based on the first subset and transmit the first control instructions to the control processor of the control device. The processor may transmit the second subset to a remote computing device. In response to transmitting the second subset to the remote computing device, the processor may receive a remote processing result from the remote computing device. The processor may generate second control instructions from the remote processing result and transmit the second control instructions to the control processor.
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公开(公告)号：US12124927B2
公开(公告)日：2024-10-22
申请号：US17449782
申请日：2021-10-01
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
IPC: G06F11/30 , G01L1/22 , G01L5/1627 , G01P15/02 , G06N20/00
CPC classification number: G06N20/00 , G01L1/22 , G01L5/1627 , G01P15/02
Abstract: Examples are disclosed that relate to methods and systems for classifying a surface type. One example provides a system comprising a wearable device comprising at least one force sensor, and a computing device having a processor and associated memory storing instructions executable by the processor. The instructions are executable by the processor to, during a training phase, receive training data including a plurality of training data pairs. Each training data pair includes force sensor training data received from the at least one force sensor, or from a simulation or observation, and a label indicating at least one of a plurality of defined surface types. An AI model is trained to predict a classified surface type based on run-time force sensor data. The run-time force sensor data is input into the trained AI model to thereby cause the AI model to output a predicted classification of a run-time surface type.
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Patent Agency Ranking
公开(公告)号：US12014514B2
公开(公告)日：2024-06-18
申请号：US17647309
申请日：2022-01-06
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
IPC: G06T7/70 , G06F3/0484 , G06V10/764 , G06V20/17
CPC classification number: G06T7/70 , G06F3/0484 , G06V10/764 , G06V20/17 , G06T2207/30244 , G06V2201/07
Abstract: One example provides a target classification system comprising a display subsystem configured to display an image captured by a camera of an in-field device. The image includes one or more targets. The target classification system is configured to receive a user input indicating a location of the one or more targets in a screen space coordinate system of the display subsystem. Location information in a world space coordinate system is determined by receiving a pose of the camera; using the pose of the camera and the location in the screen space to trace a ray; and using at least a position of the camera and an orientation of the ray to generate coordinates in the world space. Target classification information is determined, and targeting data is output comprising the coordinates in the world space and the target classification information.
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公开(公告)号：US20230033838A1
公开(公告)日：2023-02-02
申请号：US17390676
申请日：2021-07-30
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
Abstract: Examples are disclosed that relate to methods, computing devices, and systems for determining a user's readiness for an operational task. One example provides a method comprising, during a training phase, receiving training input data including, for each user training session, a training data pair including, as input, a distance of travel, a mode of travel, and one or more environmental conditions, and as ground truth output, a time elapsed for performance of the training task. An artificial intelligence (AI) performance model is trained to model user performance of the training task based on the training data pairs. During a run-time phase, operational input data is received that is associated with an operational task performed by the user. The performance model is used to infer a predicted time elapsed for performance of the operational task.
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公开(公告)号：US11550277B2
公开(公告)日：2023-01-10
申请号：US17247919
申请日：2020-12-30
Applicant: MORPHIX, INC.
Inventor： Jonathan Lovegrove
IPC: H01R27/00 , G05B19/04 , G05B19/045 , G05B19/048 , H04L67/125 , G16Y20/20 , G16Y40/35 , G16Y10/25 , G16Y20/10 , H01R13/639 , H01R13/52 , H01R13/73
Abstract: A ruggedized edge computing assembly is provided, which includes an edge computing device having a processor configured to control a controlled device. The ruggedized edge computing assembly includes a field connector configured to connect to the edge computing device via a plurality of pins and to the controlled device via a coupling. The ruggedized edge computing assembly further includes a housing overmolded around each of the field connector and the edge computing device. The housing includes two portions which are a field connector portion configured to accommodate the field connector and an edge computing device portion configured to accommodate the edge computing device. The two portions are configured to interlockingly engage together at an interface.
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公开(公告)号：US20240420027A1
公开(公告)日：2024-12-19
申请号：US18821346
申请日：2024-08-30
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
IPC: G06N20/00 , G01L1/22 , G01L5/1627 , G01P15/02
Abstract: Examples are disclosed that relate to methods and systems for classifying a surface type. One example provides a system comprising a wearable device comprising at least one force sensor, and a computing device having a processor and associated memory storing instructions executable by the processor. The instructions are executable by the processor to, during a training phase, receive training data including a plurality of training data pairs. Each training data pair includes force sensor training data received from the at least one force sensor, or from a simulation or observation, and a label indicating at least one of a plurality of defined surface types. An AI model is trained to predict a classified surface type based on run-time force sensor data. The run-time force sensor data is input into the trained AI model to thereby cause the AI model to output a predicted classification of a run-time surface type.
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公开(公告)号：US20240123286A1
公开(公告)日：2024-04-18
申请号：US18397900
申请日：2023-12-27
Applicant: Morphix, Inc.
Inventor： Jonathan Lovegrove
CPC classification number: A63B24/0062 , A63B71/0622 , G06N20/00 , A63B2024/0068 , A63B2220/62 , A63B2220/70 , A63B2220/836
Abstract: Examples are disclosed that relate to methods, computing devices, and systems for determining a user's readiness for an operational task. One example provides a method comprising, during a training phase, receiving training input data including, for each user training session, a training data pair including, as input, a distance of travel, a mode of travel, and one or more environmental conditions, and as ground truth output, a time elapsed for performance of the training task. An artificial intelligence (AI) performance model is trained to model user performance of the training task based on the training data pairs. During a run-time phase, operational input data is received that is associated with an operational task performed by the user. The performance model is used to infer a predicted time elapsed for performance of the operational task.
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