Abstract: Aspects of the disclosure relate to identifying and responding to problem conditions for a fleet of aerial vehicles. This may include receiving at one or more processors of one or more server computing devices sensor feedback from an AV of the fleet. A problem condition may be identified using the sensor feedback. A mitigation response for the problem condition relating to a mission assigned to the aerial vehicle may be determined. The mitigation response may be sent to the AV in order to cause the aerial vehicle to maneuver according to the mitigation response and thereby automatically respond to the problem condition.

Abstract: Controlling a vehicle according to a trained neural network model capable of being used to generate an output from which one or more vehicle operating variables can be estimated. The neural network model can be used to process, as input, aggregated data corresponding to operational and/or environmental characteristics experienced by the vehicle during at least a portion of a voyage. The aggregated data can include a range of values collected over a period of time when the vehicle is traversing the portion of the voyage. The output generated by the neural network model, based on processing the input, can be further processed in order to determine, for example, an estimated state of charge and/or an estimated remaining flight time for the vehicle. Such estimated values can thereafter be used by a controller of the vehicle to maintain course or maneuver to a charging station.

Abstract: Disclosed herein are methods and systems that can help an aerial transport service provider (ATSP) select an unmanned vehicle (UV) to deliver a temperature-sensitive item. In accordance with example embodiments, the ATSP system can generate a transport task to fulfill a request for delivery of the temperature-sensitive item, where the transport task involves delivering the item while maintaining a temperature of the item within a preferred temperature range. The system can calculate an amount of required energy to perform the transport task for each available UV of the fleet of UVs. Further, based on (i) the amount of required energy for each available UV, and (ii) a respective remaining battery energy level for each available UV, the ATSP system can select a first UV to perform the task. Yet further, the ATSP system can assign the transport task to the first UV.

Abstract: Controlling a vehicle according to a trained neural network model capable of being used to generate an output from which one or more vehicle operating variables can be estimated. The neural network model can be used to process, as input, aggregated data corresponding to operational and/or environmental characteristics experienced by the vehicle during at least a portion of a voyage. The aggregated data can include a range of values collected over a period of time when the vehicle is traversing the portion of the voyage. The output generated by the neural network model, based on processing the input, can be further processed in order to determine, for example, an estimated state of charge and/or an estimated remaining flight time for the vehicle. Such estimated values can thereafter be used by a controller of the vehicle to maintain course or maneuver to a charging station.

Abstract: Controlling a vehicle according to a trained neural network model capable of being used to generate an output from which one or more vehicle operating variables can be estimated. The neural network model can be used to process, as input, aggregated data corresponding to operational and/or environmental characteristics experienced by the vehicle during at least a portion of a voyage. The aggregated data can include a range of values collected over a period of time when the vehicle is traversing the portion of the voyage. The output generated by the neural network model, based on processing the input, can be further processed in order to determine, for example, an estimated state of charge and/or an estimated remaining flight time for the vehicle. Such estimated values can thereafter be used by a controller of the vehicle to maintain course or maneuver to a charging station.

Abstract: A technique for power an apparatus during a mission includes powering the apparatus with a first energy storage device during a first mission segment of the mission. The first energy storage device has a first energy density and a first peak power rating. The apparatus is powered with a second energy storage device, distinct from the first energy storage device, during a second mission segment of the mission. The second energy storage device has a second energy density lower than the first energy density and a second peak power rating that is greater than the first peak power rating.

Abstract: An aerial vehicle may include a control unit configured to send control signals in order to control flight of the aerial vehicle, propulsion units configured to control the attitude of the aerial vehicle, propulsion controllers configured to send commands to a corresponding propulsion unit of the propulsion units based on the control signals, and inertial measurement units (IMU). Each of the IMUs is configured to provide attitude information to a corresponding one of the propulsion controllers. In this way, there is one propulsion controller for each of the propulsion units and one IMU for each of the propulsion controllers. When there is a failure at the control unit, each of the propulsion control unit units are configured automatically generate the commands and control the propulsion units in order to attempt to stabilize the aerial vehicle.

Abstract: Controlling a vehicle according to a trained neural network model capable of being used to generate an output from which one or more vehicle operating variables can be estimated. The neural network model can be used to process, as input, aggregated data corresponding to operational and/or environmental characteristics experienced by the vehicle during at least a portion of a voyage. The aggregated data can include a range of values collected over a period of time when the vehicle is traversing the portion of the voyage. The output generated by the neural network model, based on processing the input, can be further processed in order to determine, for example, an estimated state of charge and/or an estimated remaining flight time for the vehicle. Such estimated values can thereafter be used by a controller of the vehicle to maintain course or maneuver to a charging station.

Abstract: In an embodiment, an apparatus includes a plurality of electrical contacts, wherein first and second electrical contacts of the plurality of electrical contacts electrically couple with a charging device; one or more rechargeable batteries configured to be charged from power received, via the first and second electrical contacts, from the charging device; and circuitry configured to obtain battery state information associated with the one or more rechargeable batteries during charging of the one or more rechargeable batteries and generate battery charge rate data based on the battery state information. At least one of the first and second electrical contacts is configured to transmit the battery charge rate data to the charging device, and the battery charge rate data is configured to be used by the charging device to regulate charging of the one or more rechargeable batteries.

Abstract: In an embodiment, an apparatus includes a plurality of electrical contacts, wherein first and second electrical contacts of the plurality of electrical contacts electrically couple with a charging device; one or more rechargeable batteries configured to be charged from power received, via the first and second electrical contacts, from the charging device; and circuitry configured to obtain battery state information associated with the one or more rechargeable batteries during charging of the one or more rechargeable batteries and generate battery charge rate data based on the battery state information. At least one of the first and second electrical contacts is configured to transmit the battery charge rate data to the charging device, and the battery charge rate data is configured to be used by the charging device to regulate charging of the one or more rechargeable batteries.

Abstract: An aerial vehicle may include a control unit configured to send control signals in order to control flight of the aerial vehicle, propulsion units configured to control the attitude of the aerial vehicle, propulsion controllers configured to send commands to a corresponding propulsion unit of the propulsion units based on the control signals, and inertial measurement units (IMU). Each of the IMUs is configured to provide attitude information to a corresponding one of the propulsion controllers. In this way, there is one propulsion controller for each of the propulsion units and one IMU for each of the propulsion controllers. When there is a failure at the control unit, each of the propulsion control unit units are configured automatically generate the commands and control the propulsion units in order to attempt to stabilize the aerial vehicle.

Abstract: Disclosed herein are methods and systems that can help an aerial transport service provider (ATSP) select an unmanned vehicle (UV) to deliver a temperature-sensitive item. In accordance with example embodiments, the ATSP system can generate a transport task to fulfill a request for delivery of the temperature-sensitive item, where the transport task involves delivering the item while maintaining a temperature of the item within a preferred temperature range. The system can calculate an amount of required energy to perform the transport task for each available UV of the fleet of UVs. Further, based on (i) the amount of required energy for each available UV, and (ii) a respective remaining battery energy level for each available UV, the ATSP system can select a first UV to perform the task. Yet further, the ATSP system can assign the transport task to the first UV.

Abstract: A technique for power an apparatus during a mission includes powering the apparatus with a first energy storage device during a first mission segment of the mission. The first energy storage device has a first energy density and a first peak power rating. The apparatus is powered with a second energy storage device, distinct from the first energy storage device, during a second mission segment of the mission. The second energy storage device has a second energy density lower than the first energy density and a second peak power rating that is greater than the first peak power rating.

Abstract: Aspects of the disclosure relate to identifying and responding to problem conditions for a fleet of aerial vehicles. This may include receiving at one or more processors of one or more server computing devices sensor feedback from an AV of the fleet. A problem condition may be identified using the sensor feedback. A mitigation response for the problem condition relating to a mission assigned to the aerial vehicle may be determined. The mitigation response may be sent to the AV in order to cause the aerial vehicle to maneuver according to the mitigation response and thereby automatically respond to the problem condition.

Abstract: A system for secure user authentication of a mobile electronic device includes a touch-based user interface of the mobile electronic device, a processor, and a computer-readable storage medium. The system presents a graphical user interface comprising a target location represented by a graphical indication, and receives an authentication code comprising a sequence of taps. The system determines input positional data associated with the authentication code that indicates a location on the touch-based user interface where the sequence of taps is received. The system determines whether to permit a user of the mobile electronic device to access a function of the mobile electronic device based at least in part on whether the input positional data is consistent with previous input received from the user of the mobile electronic device.

Abstract: A system for secure user authentication of a mobile electronic device includes a touch-based user interface of the mobile electronic device, a processor, and a computer-readable storage medium. The system presents a graphical user interface comprising a target location represented by a graphical indication, and receives an authentication code comprising a sequence of taps. The system determines input positional data associated with the authentication code that indicates a location on the touch-based user interface where the sequence of taps is received. The system determines whether to permit a user of the mobile electronic device to access a function of the mobile electronic device based at least in part on whether the input positional data is consistent with previous input received from the user of the mobile electronic device.