Patents by Inventor Andrew Musto

Andrew Musto has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11693407
    Abstract: An aircrew automation system that provides a pilot with high-fidelity knowledge of the aircraft's physical state, and notifies that pilot of any deviations in expected state based on predictive models. The aircrew automation may be provided as a non-invasive ride-along aircrew automation system that perceives the state of the aircraft through visual techniques, derives the aircraft state vector and other aircraft information, and communicates any deviations from expected aircraft state to the pilot.
    Type: Grant
    Filed: May 4, 2020
    Date of Patent: July 4, 2023
    Assignee: The Boeing Company
    Inventors: Jessica E. Duda, John Tylko, David Mindell, Fabrice Kunzi, Michael Piedmonte, John Allee, Joshua Torgerson, Jason Ryan, James Donald Paduano, John Brooke Wissler, Andrew Musto, Wendy Feenstra
  • Patent number: 11151810
    Abstract: An adaptable vehicle monitoring system is disclosed. The system includes a core platform having a state monitoring subsystem and a feedback subsystem. The core platform interconnects a perception subsystem, a knowledge acquisition subsystem, and a user interface. The perception subsystem is configured to acquire current vehicle state data from instruments of a vehicle. The knowledge acquisition subsystem includes a context awareness subsystem configured to determine a current vehicle context. The state monitoring subsystem is configured to derive a current vehicle state based at least in part on the vehicle state data and vehicle context. The knowledge acquisition subsystem further includes a database subsystem configured to store the current vehicle state data, current vehicle context, and current vehicle state. The trend monitoring subsystem is configured to analyze the one or more stored vehicle state data, stored vehicle contexts, and stored vehicle states to identify one or more trends.
    Type: Grant
    Filed: October 12, 2018
    Date of Patent: October 19, 2021
    Assignee: Aurora Flight Sciences Corporation
    Inventors: Jason Christopher Ryan, Jessica Edmonds Duda, Andrew Musto
  • Publication number: 20200301422
    Abstract: An aircrew automation system that provides a pilot with high-fidelity knowledge of the aircraft's physical state, and notifies that pilot of any deviations in expected state based on predictive models. The aircrew automation may be provided as a non-invasive ride-along aircrew automation system that perceives the state of the aircraft through visual techniques, derives the aircraft state vector and other aircraft information, and communicates any deviations from expected aircraft state to the pilot.
    Type: Application
    Filed: May 4, 2020
    Publication date: September 24, 2020
    Inventors: Jessica E. Duda, John Tylko, David Mindell, Fabrice Kunzi, Michael Piedmonte, John Allee, Joshua Torgerson, Jason Ryan, James Donald Paduano, John Brooke Wissler, Andrew Musto, Wendy Feenstra
  • Patent number: 10642270
    Abstract: An aircrew automation system and method for use in an aircraft. The aircrew automation system comprises one or more processors, an optical perception system, an actuation system, and a human-machine interface. The optical perception system monitors, in real-time, one or more cockpit instruments of the aircraft visually to generate flight situation data. The actuation system mechanically engages at least one flight control of the aircraft in response to the one or more flight commands. The human-machine interface provides an interface between a human pilot and the aircrew automation system. The human-machine interface comprises a display device to display a status of the aircraft and the actuation system.
    Type: Grant
    Filed: July 8, 2019
    Date of Patent: May 5, 2020
    Assignee: Aurora Flight Sciences Corporation
    Inventors: Jessica E. Duda, John Tylko, David Mindell, Fabrice Kunzi, Michael Piedmonte, John Allee, Joshua Torgerson, Jason Ryan, James Donald Paduano, John Brooke Wissler, Andrew Musto, Wendy Feenstra
  • Publication number: 20200118366
    Abstract: An adaptable vehicle monitoring system is disclosed. The system includes a core platform having a state monitoring subsystem and a feedback subsystem. The core platform interconnects a perception subsystem, a knowledge acquisition subsystem, and a user interface. The perception subsystem is configured to acquire current vehicle state data from instruments of a vehicle. The knowledge acquisition subsystem includes a context awareness subsystem configured to determine a current vehicle context. The state monitoring subsystem is configured to derive a current vehicle state based at least in part on the vehicle state data and vehicle context. The knowledge acquisition subsystem further includes a database subsystem configured to store the current vehicle state data, current vehicle context, and current vehicle state. The trend monitoring subsystem is configured to analyze the one or more stored vehicle state data, stored vehicle contexts, and stored vehicle states to identify one or more trends.
    Type: Application
    Filed: October 12, 2018
    Publication date: April 16, 2020
    Inventors: Jason Christopher Ryan, Jessica Edmonds Duda, Andrew Musto
  • Publication number: 20200064840
    Abstract: An aircrew automation system and method for use in an aircraft. The aircrew automation system comprises one or more processors, an optical perception system, an actuation system, and a human-machine interface. The optical perception system monitors, in real-time, one or more cockpit instruments of the aircraft visually to generate flight situation data. The actuation system mechanically engages at least one flight control of the aircraft in response to the one or more flight commands. The human-machine interface provides an interface between a human pilot and the aircrew automation system. The human-machine interface comprises a display device to display a status of the aircraft and the actuation system.
    Type: Application
    Filed: July 8, 2019
    Publication date: February 27, 2020
    Inventors: Jessica E. Duda, John Tylko, David Mindell, Fabrice Kunzi, Michael Piedmonte, John Allee, Joshua Torgerson, Jason Ryan, James Donald Paduano, John Brooke Wissler, Andrew Musto, Wendy Feenstra
  • Patent number: 10359779
    Abstract: An aircrew automation system that provides a pilot with high-fidelity knowledge of the aircraft's physical state, and notifies that pilot of any deviations in expected state based on predictive models. The aircrew automation may be provided as a non-invasive ride-along aircrew automation system that perceives the state of the aircraft through visual techniques, derives the aircraft state vector and other aircraft information, and communicates any deviations from expected aircraft state to the pilot.
    Type: Grant
    Filed: March 21, 2017
    Date of Patent: July 23, 2019
    Assignee: Aurora Flight Sciences Corporation
    Inventors: Jessica E. Duda, John Tylko, David Mindell, Fabrice Kunzi, Michael Piedmonte, John Allee, Joshua Torgerson, Jason Ryan, James Donald Paduano, John Brooke Wissler, Andrew Musto, Wendy Feenstra
  • Publication number: 20170277185
    Abstract: An aircrew automation system that provides a pilot with high-fidelity knowledge of the aircraft's physical state, and notifies that pilot of any deviations in expected state based on predictive models. The aircrew automation may be provided as a non-invasive ride-along aircrew automation system that perceives the state of the aircraft through visual techniques, derives the aircraft state vector and other aircraft information, and communicates any deviations from expected aircraft state to the pilot.
    Type: Application
    Filed: March 21, 2017
    Publication date: September 28, 2017
    Inventors: Jessica E. Duda, John Tylko, David Mindell, Fabrice Kunzi, Michael Piedmonte, John Allee, Joshua Torgerson, Jason Ryan, James Donald Paduano, John Brooke Wissler, Andrew Musto, Wendy Feenstra