Abstract: An unmanned aerial vehicle includes a camera, one or more sensors, memory storing first instructions that define an overall mission, and memory storing one or more mission cues. The vehicle further includes one or more processors configured to execute a first part of the first instructions to perform a first part of the overall mission. The processors are configured to process at least one of the image data and the sensor data to detect a presence of at least one of the mission cues. The processors are configured to, in response to detecting a mission cue, interrupting execution of the first instructions and executing second instructions to control the unmanned aerial vehicle to perform a first sub-mission of the overall mission. The processors are configured to after executing the second instructions, performing a second part of the overall mission by executing a second part of the first instructions.

Abstract: An unmanned aerial vehicle includes a camera, one or more sensors, memory storing first instructions that define an overall mission, and memory storing one or more mission cues. The vehicle further includes one or more processors configured to execute a first part of the first instructions to perform a first part of the overall mission. The processors are configured to process at least one of the image data and the sensor data to detect a presence of at least one of the mission cues. The processors are configured to, in response to detecting a mission cue, interrupting execution of the first instructions and executing second instructions to control the unmanned aerial vehicle to perform a first sub-mission of the overall mission. The processors are configured to after executing the second instructions, performing a second part of the overall mission by executing a second part of the first instructions.

Abstract: A first mobile device or other portable computer receives an originally unified or previously combined data set and algorithmically processing at least two portions of the data set by different algorithmic processes and displaying the resultant information in an enhanced imaging on a video screen of the first device. The original data set can be preprocessed by a second device, and the resultant information generated in this data preprocessing by the second computational device is provided to the first device for additional processing and display to a user. The first device applies an alternate and distinctively different second algorithmic process to the resultant information and/or the original data set to generate a second information, whereupon the first device visually presents (a.) elements of the second information; (b.) elements of the resultant information as generated by the second device; and/or (c.) some or all of the original data set.

Abstract: Structure inspections are performed with a high resolution by first performing a modeling flight path at a relatively high altitude over the structure. Images are gathered during the modeling flight path and are used to generate a three dimensional model of the structure. From the three dimensional model a lower altitude closer inspection flight path is defined and executed.

Abstract: Provided herein are systems and methods for providing reliable control of an unmanned aerial vehicle (UAV). A system for providing reliable control of the UAV can include a computing device that can execute reliable and unreliable programs. The unreliable programs can be isolated from the reliable programs by virtue of executing one or more of the programs in a virtual machine client. The UAV can initiate a recovery action when one or more of the unreliable programs fail. The recovery action can be performed without input from one or more of the unreliable programs.

Abstract: An unmanned aerial vehicle includes a camera, one or more sensors, memory storing first instructions that define an overall mission, and memory storing one or more mission cues. The vehicle further includes one or more processors configured to execute a first part of the first instructions to perform a first part of the overall mission. The processors are configured to process at least one of the image data and the sensor data to detect a presence of at least one of the mission cues. The processors are configured to, in response to detecting a mission cue, interrupting execution of the first instructions and executing second instructions to control the unmanned aerial vehicle to perform a first sub-mission of the overall mission. The processors are configured to after executing the second instructions, performing a second part of the overall mission by executing a second part of the first instructions.

Abstract: An unmanned aerial vehicle includes a camera, one or more sensors, memory storing first instructions that define an overall mission, and memory storing one or more mission cues. The vehicle further includes one or more processors configured to execute a first part of the first instructions to perform a first part of the overall mission. The processors are configured to process at least one of the image data and the sensor data to detect a presence of at least one of the mission cues. The processors are configured to, in response to detecting a mission cue, interrupting execution of the first instructions and executing second instructions to control the unmanned aerial vehicle to perform a first sub-mission of the overall mission. The processors are configured to after executing the second instructions, performing a second part of the overall mission by executing a second part of the first instructions.

Abstract: Structure inspections are performed with a high resolution by first performing a modeling flight path at a relatively high altitude over the structure. Images are gathered during the modeling flight path and are used to generate a three dimensional model of the structure. From the three dimensional model a lower altitude closer inspection flight path is defined and executed.

Abstract: An unmanned aerial vehicle is provided, including a primary operation system in communication with a primary state estimator. The primary operation system is configured to operate the unmanned aerial vehicle based in part on the primary state estimator. The vehicle includes a flight failure recovery system in communication with a recovery state estimator and the primary operation system. The flight failure recovery system is configured to determine, at a first time, that flight failure has occurred. The flight failure recovery system is configured to determine a suitable second time to generate a deploy signal for a parachute based at least in part on one or more signals from the recovery state estimator. There is a delay between the first time and the suitable second time. An intelligent emergency parachute deployment system for, and a method for flight failure recovery of an unmanned aerial vehicle are also provided.

Abstract: An unmanned aerial vehicle includes a camera, one or more sensors, memory storing first instructions that define an overall mission, and memory storing one or more mission cues. The vehicle further includes one or more processors configured to execute a first part of the first instructions to perform a first part of the overall mission. The processors are configured to process at least one of the image data and the sensor data to detect a presence of at least one of the mission cues. The processors are configured to, in response to detecting a mission cue, interrupting execution of the first instructions and executing second instructions to control the unmanned aerial vehicle to perform a first sub-mission of the overall mission. The processors are configured to after executing the second instructions, performing a second part of the overall mission by executing a second part of the first instructions.

Abstract: An unmanned aerial vehicle responds to mission cues during a mission. The mission cues are characteristics of image and/or sensor data. The unmanned aerial vehicle may change data gathering operations or may perform sub-missions within a mission in response to the mission cues.

Abstract: An unmanned aerial vehicle includes a closely integrated emergency recovery and operation systems for an unmanned aerial vehicle with built-in levels of redundancy and independence to maximize the likelihood of a controlled velocity landing. The unmanned aerial vehicle may include multiple processors and multiple state estimating modules such as inertial measurement units to independently determine the operational and error status of the unmanned aerial vehicle. Base on predictive or projected computations, the emergency recovery system may determine a suitable time for a recovery action, such as parachute deployment, and execute the recovery action.

Abstract: Topology based adaptive data gathering is disclosed herein. Payload data gathering by an unmanned aerial vehicle can be adjusted based on topological or topographical characteristics of the area of flight by the unmanned aerial vehicle. The unmanned aerial vehicle collects payload data over an area and may scale up the rate of payload data gathering or slow down the flight as the unmanned aerial vehicle flies over a high or complex structure. Conversely, the unmanned aerial vehicle may advantageously scale down the rate of payload data gathering or speed up the flight as the unmanned aerial vehicle flies over a simple structure or an empty area.

Abstract: Provided herein are systems and methods for providing reliable control of an unmanned aerial vehicle (UAV). A system for providing reliable control of the UAV can include a computing device that can execute reliable and unreliable programs. The unreliable programs can be isolated from the reliable programs by virtue of executing one or more of the programs in a virtual machine client. The UAV can initiate a recovery action when one or more of the unreliable programs fail. The recovery action can be performed without input from one or more of the unreliable programs.

Abstract: An unmanned aerial vehicle responds to mission cues during a mission. The mission cues are characteristics of image and/or sensor data. The unmanned aerial vehicle may change data gathering operations or may perform sub-missions within a mission in response to the mission cues.

Abstract: Provided herein are systems and methods for providing reliable control of an unmanned aerial vehicle (UAV). A system for providing reliable control of the UAV can include a computing device that can execute reliable and unreliable programs. The unreliable programs can be isolated from the reliable programs by virtue of executing one or more of the programs in a virtual machine client. The UAV can initiate a recovery action when one or more of the unreliable programs fail. The recovery action can be performed without input from one or more of the unreliable programs.

Abstract: A data communication system for unmanned aerial vehicles includes communication links comprising a low-throughput capacity communication link and a high-throughput capacity communication link. The data communication system can also include a base station, to which the unmanned aerial vehicles send aerial data, and from which the unmanned aerial vehicles receive command signals. As the unmanned aerial vehicles perform missions in an open, distant airspace, the unmanned aerial vehicles can gather large volume data such as aerial images or videos. The data communication system allows opportunistic transfer of the gathered aerial data from the unmanned aerial vehicles to the base station when a high-throughput communication link is established. The data communication system allows constant communication between the base station and the unmanned aerial vehicles to send and receive low volume, operation-critical data, such as commands or on-going flight path changes, using a low-throughput communication link.

Abstract: Topology based adaptive data gathering is disclosed herein. Payload data gathering by an unmanned aerial vehicle can be adjusted based on topological or topographical characteristics of the area of flight by the unmanned aerial vehicle. The unmanned aerial vehicle collects payload data over an area and may scale up the rate of payload data gathering or slow down the flight as the unmanned aerial vehicle flies over a high or complex structure. Conversely, the unmanned aerial vehicle may advantageously scale down the rate of payload data gathering or speed up the flight as the unmanned aerial vehicle flies over a simple structure or an empty area.

Abstract: The disclosure herein describes methods and apparatuses for magnetometer calibration through collection and processing of calibration data in the background and unassisted autonomous calibration maneuvers prior to a mission. As an autonomous or semi-autonomous vehicle is transported by the user after power up, vehicle data relevant to magnetometer calibration can be collected from the movements of the vehicle. Magnetometer calibration accuracy checks or some parts of magnetometer calibration can be performed from the data collected in the background. Based on the extent of accuracy determinations, the vehicle can further perform autonomous and unassisted maneuvers to complete magnetometer calibration before performing a mission.

Abstract: An enhanced distance detection system for an autonomous or semi-autonomous vehicle is described here. The distance detection system includes a distance detector, which may have a limited scope of distance detection, and a directional controller, which allows extending the dimension or scope of the distance detector as the vehicle travels and performs missions. The directional controller can change the detection direction of the distance detector with a motorized gimbal or functionally similar system, and the change in the detection direction can be integrated with the status of and other instructions executed by the vehicle.