A repellence system and method for repelling animals. The repellence system includes an imaging device arranged to generate image data from a surveillance area, one or more deterrence devices arranged to carry out deterrence actions for repelling animals and an repellence sub-system having one or more processors and memory storing instructions for execution by the one or more processors. The repellence sub-system being configured to receive image data of the surveillance area from the imaging device, detect an animal in the image data, identify animal species of the detected animal in the image data, provide species specific deterrence instructions to the one or more deterrence devices based on the identified animal species.

A repellence system and method for repelling animals. The repellence system includes an imaging device arranged to generate image data from a surveillance area, one or more deterrence devices arranged to carry out deterrence actions for repelling animals and an repellence sub-system having one or more processors and memory storing instructions for execution by the one or more processors. The repellence sub-system being configured to receive image data of the surveillance area from the imaging device, detect an animal in the image data, identify animal species of the detected animal in the image data, provide species specific deterrence instructions to the one or more deterrence devices based on the identified animal species.

There is provided a computerized method of controlling ascent of an underwater vehicle (UV) from a safety depth to a water surface, the method comprising: at safety depth, controlling the UV to collect, from a passive sonar associated with the UV, first data indicative of first locations of surface targets within a first surface area of interest; controlling ascent of the UV to an intermediate depth in accordance with the first data; at the intermediate depth, controlling the UV to collect second data indicative of second locations of surface targets within a second surface area of interest, wherein the second data comprises one or more of: data from a passive sonar, data from one or more magnetic sensors, data from an active sonar, data from a light detection and ranging (LIDAR) scanner; and controlling ascent of the UV to a periscope depth in accordance with the second data.

There is provided a computerized method of controlling ascent of an underwater vehicle (UV) from a safety depth to a water surface, the method comprising: at safety depth, controlling the UV to collect, from a passive sonar associated with the UV, first data indicative of first locations of surface targets within a first surface area of interest; controlling ascent of the UV to an intermediate depth in accordance with the first data; at the intermediate depth, controlling the UV to collect second data indicative of second locations of surface targets within a second surface area of interest, wherein the second data comprises one or more of: data from a passive sonar, data from one or more magnetic sensors, data from an active sonar, data from a light detection and ranging (LIDAR) scanner; and controlling ascent of the UV to a periscope depth in accordance with the second data.

In accordance with some embodiments, a system for controlling an aircraft is provided. The system can include a computing device, wherein the computing device includes at least one processor configured to control a flight path angle of the aircraft, and wherein the aircraft is a blown lift aircraft. The system can also include a control operator communicatively coupled to the computing device, wherein the control operator is configured to have at least two selectable settings. The system can also include at least two thrust-producing devices operatively coupled to a pair of wings on the aircraft and communicatively coupled to the computing device. The computing device may control the flight path angle of the aircraft by selectively operating the at least two thrust-producing devices based on a plurality of conditions provided by a plurality of sensors on the aircraft and a selected setting of the control operator.

In accordance with some embodiments, a system for controlling an aircraft is provided. The system can include a computing device, wherein the computing device includes at least one processor configured to control a flight path angle of the aircraft, and wherein the aircraft is a blown lift aircraft. The system can also include a control operator communicatively coupled to the computing device, wherein the control operator is configured to have at least two selectable settings. The system can also include at least two thrust-producing devices operatively coupled to a pair of wings on the aircraft and communicatively coupled to the computing device. The computing device may control the flight path angle of the aircraft by selectively operating the at least two thrust-producing devices based on a plurality of conditions provided by a plurality of sensors on the aircraft and a selected setting of the control operator.

A dual agent reinforcement learning autonomous system (DARLAS) for the autonomous operation of aircraft and/or provide pilot assistance. DARLAS includes an artificial neural network, safe agent, and cost agent. The safe agent is configured to calculate safe reward Q values associated with landing the aircraft at a predetermined destination or calculated emergency destination. The cost agent is configured to calculate cost reward Q values associated with maximum fuel efficiency and aircraft performance. The safe and cost reward Q values are based on state-action vectors associated with an aircraft, which may include state data and action data. The system may include a user output device that provides an indication of an action to a user. The action corresponds to an agent action having the highest safe reward Q value and the highest cost require Q value. DARLAS prioritizes the highest safe reward Q value in the event of conflict.

A system and a method for operating an aircraft during a climb phase of flight include a control unit configured to receive data regarding one or both of a current flight or one or more previous flights of the aircraft from one or more sensors of the aircraft. The control unit is further configured to determine efficient climb phase parameters for the aircraft based on the data. The aircraft is operated during the climb phase of one or both of the current flight or one or more future flights according to the efficient climb phase parameters.

A method includes capturing, by a sensor on an unmanned aerial vehicle (UAV), an image of a delivery location. The method also includes determining, based on the image of the delivery location, a segmentation image. The segmentation image segments the delivery location into a plurality of pixel areas with corresponding semantic classifications. The method additionally includes determining, based on the segmentation image, a percentage of obstacle pixels within a surrounding area of a delivery point at the delivery location, wherein each obstacle pixel has a semantic classification indicative of an obstacle in the delivery location. The method further includes based on the percentage of obstacle pixels being above a threshold percentage, aborting a delivery process of the UAV.

A control device controls a flight of an eVTOL including a rotary wing which is driven by a driving device to generate a rotational lift, a fixed wing which generates a gliding lift, and a lift adjustment mechanism which adjusts the gliding lift. The control device includes a rotary wing control unit which adjusts the rotational lift by controlling driving of the rotary wing, and a fixed wing control unit which adjusts the gliding lift by controlling driving of the lift adjustment mechanism. When an abnormality of the driving device is predicted or detected in a flight time of an electric flight vehicle, the rotary wing control unit and the fixed wing control unit perform lift adjustment control such that the rotary wing control unit reduces the rotational lift and the fixed wing control unit increases the gliding lift.