The present disclosure is directed to systems and methods for trajectory and route planning including obstacle detection and avoidance for an aerial vehicle. For example, an aerial vehicle's flight control system may include a trajectory planner that may use short segments calculated using an iterative Dubins path to find a first path between a start point and an end point that does not avoid obstacles. Then the trajectory planner may use a rapidly exploring random tree algorithm that uses points along the first path as seed points to find a trajectory or route between the start point and end point that avoids known or detected obstacles.

This disclosure describes systems and methods for a multipoint cable cam (MPCC) of an aerial vehicle. A method includes operations of receiving user input associated with a predetermined path and correlating the received user input with stored global positioning satellite (GPS) data to generate one or more virtual waypoints along the predetermined path. The method includes processing the one or more virtual waypoints to generate a spline-based flight path. The method may include storing the spline-based flight path and transmitting the spline-based flight path to the aerial vehicle.

Integration between unmanned aerial system and unmanned ground robotic vehicle are disclosed herein. One variation of a robotic system may generally comprise an unmanned aerial vehicle (UAV), an unmanned ground vehicle (UGV), and a base station configured to receive the UAV and replace a spent power supply cartridge from the UAV and further having a charging mechanism configured to wirelessly transfer power to the UGV when the UGV is positioned in proximity to the charging pad.

A method for controlling an aircraft when taxiing comprising the steps of: measuring an angle of rotation of an active side stick about a first axis and a second axis; receiving an aircraft signal representative of an actual state of the aircraft; generating a control signal based on at least one of: the aircraft signal and the angle of rotation of the active side stick about a first axis and a second axis; transmitting the control signal to the aircraft, whereby the control signal causes an action affecting the actual state of the aircraft; determining a required state of the aircraft; generating a user feedback signal based on at least one difference between the actual state and the required state; and carrying out a user feedback action based on the user feedback signal.

A method for supporting aerial operation over a surface includes obtaining a three-dimensional (3D) representation of the surface; converting the 3D representation of the surface to a two-dimensional (2D) representation of the surface; obtaining a 2D flight path of the aircraft based on the 2D representation of the surface; converting the 2D flight path to a 3D flight path including location coordinates; and controlling the aircraft to conduct a flight mission following the 3D flight path.

A system for displaying videos, comprising a processing resource configured to: provide a data repository comprising a plurality of previously captured video segments (PCVSs) captured during previous operations of corresponding platforms, each being associated with metadata indicative of a Line-of-Sight (LoS) of a sensor, carried by the corresponding platform of the platforms used to capture the corresponding PCVS, with respect to a fixed coordinate system established in space, during capturing the corresponding PCVS; obtain an indication of a Region-of-Interest (RoI); identify one or more of the PCVSs that include at least part of the RoI, utilizing the LoSs associated with the PCVSs, giving rise to RoI matching PCVSs; and display at least part of at least one of the RoI matching PCVSs, being displayed RoI matching PCVSs, on a display of an operating platform to an operator of the operating platform during a current operation of the operating platform.

A method is provided for detecting and avoiding conflict during a mission of a robot that includes a global route of travel. The method includes monitoring a state of the robot and a state of an environment of the robot as the robot travels the global route. The method includes generating a local route of travel through a region of the environment that includes the robot, the region having a size and shape that are set based on a type of the robot and the state of the robot when the local route is generated. A measure of uncertainty in the perception of objects in the region is monitored based on the state of the environment. And the robot is caused to maintain the global route or transition to the local route based on a comparison of the measure of uncertainty and an uncertainty threshold.

Vertical take-off and landing (VTOL) aircraft can provide opportunities to incorporate aerial transportation into transportation networks for cities and metropolitan areas. However, VTOL aircraft may be noisy. To accommodate this, the aircraft may utilize onboard sensors, offboard sensing, network, and predictive temporal data for noise signature mitigation. By building a composite understanding of real data offboard the aircraft, the aircraft can make adjustments to the way it is flying and verify this against a predicted noise signature (via computational methods) to reduce environmental impact. This might be realized via a change in translative speed, propeller speed, or choices in propulsor usage (e.g., a quiet propulsor vs. a high thrust, noisier propulsor). These noise mitigation actions may also be decided at the network level rather than the vehicle level to balance concerns across a city and relieve computing constraints on the aircraft.

An autonomous vehicle system includes a body and a plurality of sensors coupled to the body and configured to generate a plurality of sensor measurements corresponding to the plurality of sensors. The system also includes a control unit configured to: receive inputs from a plurality of sources wherein the plurality sources comprise the plurality of sensors, the inputs comprise the plurality of sensor measurements; determine a confidence level of each input based on other inputs; prioritize, based on the confidence level associated with each input, the inputs; generate, based on the prioritization of the inputs and the confidence level, a combined input with a combined confidence level; and determine, based on the combined input and the combined confidence level, a mission task to be performed.

A drone is provided that includes a controller, a time measurer that measures a present time, a position measurer that obtains a current position of the drone, and a storage that stores a time period for which the flight of the drone is permitted. The controller performs operations including determining a possible flight area of the drone in accordance with a difference between an end of the time period for which flight of the drone is permitted and the present time, and determining whether the drone is located within the possible flight area on the basis of the current position of the drone.