A response system may be provided. The response system may include an autonomous drone. The autonomous drone may include a processor, a memory in communication with the processor, and a sensor. The processor may be programmed to build a virtual map of a coverage area, store the virtual map in the memory, receive a deployment signal, deploy the drone in response to the deployment signal, control movement of the drone within the coverage area using the virtual map, collect sensor data of the coverage area using the sensor, and/or analyze the sensor data to generate an inventory list of the coverage area, the inventory list including a personal article within the coverage area.

A response system may be provided. The response system may include an autonomous drone. The autonomous drone may include a processor, a memory in communication with the processor, and a sensor. The processor may be programmed to build a virtual map of a coverage area, store the virtual map in the memory, receive a deployment signal, deploy the drone in response to the deployment signal, control movement of the drone within the coverage area using the virtual map, collect sensor data of the coverage area using the sensor, and/or analyze the sensor data to generate an inventory list of the coverage area, the inventory list including a personal article within the coverage area.

An automated unmanned aerial vehicle (UAV) open water beachfront hazard recognition, warning, and rescue system and processes are disclosed. The automated UAV open water beachfront hazard recognition, warning, and rescue system includes a UAV that is configured as an autonomous patrol or scout system, an automated rip current and sea animal registration system, and a mechanical rescue system to pull out or support a person in water. The automated UAV open water beachfront hazard recognition, warning, and rescue system is configured to react quickly and reach targets fast because the UAV flies in the air and takes a direct, obstruction-free path to the target.

Systems and methods for trajectory planning for an unmanned aerial vehicle. A mission specification for fulfillment by an unmanned aerial vehicle is received. The mission specification identifies a waypoint, an optimization criterion, and information identifying the unmanned aerial vehicle. It is determined whether candidate flight trajectories are available. Maneuvers from a motions library that defines available maneuvers are modeled to identify candidate flight trajectories to the waypoint which satisfy a restriction condition and do not conflict with a flight plan for another aerial vehicle. If candidate flight trajectories are available, desired flight trajectories are selected. A mission approval is submitted to a receiving party.

Systems and methods for trajectory planning for an unmanned aerial vehicle. A mission specification for fulfillment by an unmanned aerial vehicle is received. The mission specification identifies a waypoint, an optimization criterion, and information identifying the unmanned aerial vehicle. It is determined whether candidate flight trajectories are available. Maneuvers from a motions library that defines available maneuvers are modeled to identify candidate flight trajectories to the waypoint which satisfy a restriction condition and do not conflict with a flight plan for another aerial vehicle. If candidate flight trajectories are available, desired flight trajectories are selected. A mission approval is submitted to a receiving party.

A system and method include a monitoring control unit configured to compare an initial flight plan, as generated by a flight planner for an aircraft, and an assessed flight plan, as determined by air traffic control. The monitoring control unit is configured to determine one or more differences between the initial flight plan and the assessed flight plan. The monitoring control unit is configured to output a notification signal to the flight planner regarding the one or more differences between the initial flight plan and the assessed flight plan.

A system and method include a monitoring control unit configured to compare an initial flight plan, as generated by a flight planner for an aircraft, and an assessed flight plan, as determined by air traffic control. The monitoring control unit is configured to determine one or more differences between the initial flight plan and the assessed flight plan. The monitoring control unit is configured to output a notification signal to the flight planner regarding the one or more differences between the initial flight plan and the assessed flight plan.

The present disclosure provides techniques for optimized flight monitoring. A first set of traffic data for a flight is accessed. The first set of traffic data is saved in a data store. A user interface is updated to display the first set of traffic data for the flight. A second set of traffic data for the flight is received, where the second set of traffic data is received at a later time than the first set of traffic data. A progress of the flight is monitored by comparing the first and second sets of traffic data. Upon detecting a delay in the progress of the flight, the flight is highlighted on the user interface.

This disclosure provides methods, components, devices, and systems for mitigating anxiety of a passenger along a travel route while in a vehicle. Some aspects, more specifically, relate to detecting an anxiety level of a passenger during travel and implementing anxiety mitigating techniques to alleviate the anxiety. Travel anxiety can increase the stress of a passenger during travel, especially during air travel. In some aspects, a vehicle can analyze sensor data to detect a stress level of a passenger and determine a remedial action based on the stress level. Upon determining the remedial action, the vehicle can implement the remedial action so as to mitigate or alleviate the stress associated with the passenger while traveling in the vehicle.

A technique for user interaction with an autonomous unmanned aerial vehicle (UAV) is described. In an example embodiment, perception inputs from one or more sensor devices are processed to build a shared virtual environment that is representative of a physical environment. The sensor devices used to generate perception inputs can include image capture devices onboard an autonomous aerial vehicle that is in flight through the physical environment. The shared virtual environment can provide a continually updated representation of the physical environment which is accessible to multiple network-connected devices, including multiple UAVs and multiple mobile computing devices. The shared virtual environment can be used, for example, to display visual augmentations at network-connected user devices and guide autonomous navigation by the UAV.