Abstract: Sounds are generated by an aerial vehicle during operation. For example, the motors and propellers of an aerial vehicle generate sounds during operation. Disclosed are systems, methods, and apparatus for actively adjusting the position of one or more propeller blade treatments of a propeller blade of an aerial vehicle during operation of the aerial vehicle. For example, the propeller blade may have one or more propeller blade treatments that may be adjusted between two or more positions. Based on the position of the propeller blade treatments, the airflow over the propeller is altered, thereby altering the sound generated by the propeller when rotating. By altering the propeller blade treatments on multiple propeller blades of the aerial vehicle, the different sounds generated by the different propeller blades may effectively cancel, reduce, and/or otherwise alter the total sound generated by the aerial vehicle.

Abstract: Sounds are generated by an aerial vehicle during operation. For example, the motors and propellers of an aerial vehicle generate sounds during operation. Disclosed are systems, methods, and apparatus for actively adjusting the position of one or more propeller blade treatments of a propeller blade of an aerial vehicle during operation of the aerial vehicle. For example, the propeller blade may have one or more propeller blade treatments that may be adjusted between two or more positions. Based on the position of the propeller blade treatments, the airflow over the propeller is altered, thereby altering the sound generated by the propeller when rotating. By altering the propeller blade treatments on multiple propeller blades of the aerial vehicle, the different sounds generated by the different propeller blades may effectively cancel, reduce, and/or otherwise alter the total sound generated by the aerial vehicle.

Abstract: The present disclosure is directed to controlling, reducing, and/or altering sound generated by an aerial vehicle, such as an unmanned aerial vehicle (“UAV”), while the aerial vehicle is airborne. For example, one or more transducers, such as piezoelectric thin-film transducers, or carbon nanotube transducers may be applied or incorporated into or on the surface of propeller blades that are used to aerially navigate the aerial vehicle. As the propeller blade rotates and generates sound, the transducers may be activated to generate one or more anti-sounds that cancel, reduce, or otherwise modify the sound generated by the rotation of the propeller blade. The anti-sound combines with the sound and causes interference such that the combined, or net-effect, is an overall cancellation, reduction, or other modification of the sound.

Abstract: Aerial vehicles may be operated with discrete sets of propellers, which may be selected for a specific purpose or on a specific basis. The discrete sets of propellers may be operated separately or in tandem with one another, and at varying power levels. For example, a set of propellers may be selected to optimize the thrust, lift, maneuverability or efficiency of an aerial vehicle based on a position or other operational characteristic of the aerial vehicle, or an environmental condition encountered by the aerial vehicle. At least one of the propellers may be statically or dynamically imbalanced, such that the propeller emits a predetermined sound during operation. A balanced propeller may be specifically modified to cause the aerial vehicle to emit the predetermined sound by changing one or more parameters of the balanced propeller and causing the balanced propeller to be statically or dynamically imbalanced.

Abstract: Sounds are generated by an aerial vehicle during operation. For example, the motors and propellers of an aerial vehicle generate sounds during operation. Described are sound dampening materials and other propeller blade treatments that may be included in a propeller blade to alter and/or reduce the sound generated by the propeller blade as it rotates.

Abstract: The present disclosure is directed to controlling, reducing, and/or altering sound generated by an aerial vehicle, such as an unmanned aerial vehicle (“UAV”), while the aerial vehicle is airborne. For example, one or more transducers, such as piezoelectric thin-film transducers, or carbon nanotube transducers may be applied or incorporated into or on the surface of propeller blades that are used to aerially navigate the aerial vehicle. As the propeller blade rotates and generates sound, the transducers may be activated to generate one or more anti-sounds that cancel, reduce, or otherwise modify the sound generated by the rotation of the propeller blade. The anti-sound combines with the sound and causes interference such that the combined, or net-effect, is an overall cancellation, reduction, or other modification of the sound.

Abstract: Sounds are generated by an aerial vehicle during operation. For example, the motors and propellers of an aerial vehicle generate sounds during operation. Disclosed are systems, methods, and apparatus for actively adjusting the position of one or more propeller blade treatments of a propeller blade of an aerial vehicle during operation of the aerial vehicle. For example, the propeller blade may have one or more propeller blade treatments that may be adjusted between two or more positions. Based on the position of the propeller blade treatments, the airflow over the propeller is altered, thereby altering the sound generated by the propeller when rotating. By altering the propeller blade treatments on multiple propeller blades of the aerial vehicle, the different sounds generated by the different propeller blades may effectively cancel, reduce, and/or otherwise alter the total sound generated by the aerial vehicle.

Abstract: This disclosure describes an unmanned aerial vehicle that may be configured during flight to optimize for agility or efficiency.

Abstract: Noises that are to be emitted by an aerial vehicle during operations may be predicted using one or more machine learning systems, algorithms or techniques. Anti-noises having equal or similar intensities and equal but out-of-phase frequencies may be identified and generated based on the predicted noises, thereby reducing or eliminating the net effect of the noises. The machine learning systems, algorithms or techniques used to predict such noises may be trained using emitted sound pressure levels observed during prior operations of aerial vehicles, as well as environmental conditions, operational characteristics of the aerial vehicles or locations of the aerial vehicles during such prior operations. Anti-noises may be identified and generated based on an overall sound profile of the aerial vehicle, or on individual sounds emitted by the aerial vehicle by discrete sources.

Abstract: Ground effect acting on an aerial vehicle, such as an unmanned aerial vehicle, may be simulated by discharging a gas around propeller blades of the aerial vehicle while the propeller blades are rotating. For example, a gas, such as air, may be discharged at or near the tip of the propeller blades with enough velocity to disrupt the airflow around the blade tips, thereby altering the sound generated by rotation of the propeller blade.

Abstract: An unmanned aerial vehicle (UAV) may emit masking sounds during operation of the UAV to mask other sounds generated by the UAV during operation. The UAV may be used to deliver items to a residence or other location associated with a customer. The UAV may emit sounds that mask the conventional sounds generated by the propellers and/or motors to cause the UAV to emit sounds that are pleasing to bystanders or do not annoy the bystanders. The UAV may emit sounds using speakers or other sound generating devices, such as fins, reeds, whistles, or other devices which may cause sound to be emitted from the UAV. Noise canceling algorithms may be used to cancel at least some of the conventional noise generated by operation of the UAV using inverted sounds, while additional sound may be emitted by the UAV, which may not be subject to noise cancelation.

Abstract: This disclosure describes an unmanned aerial vehicle (“UAV”) configured to autonomously deliver items of inventory to various destinations. The UAV may receive inventory information and a destination location and autonomously retrieve the inventory from a location within a materials handling facility, compute a route from the materials handling facility to a destination and travel to the destination to deliver the inventory.

Abstract: A motor mount assembly is provided for coupling a propeller motor to a body of an unmanned aerial vehicle (UAV). The motor mount assembly includes a floating portion and acts to attenuate frequencies of vibration from the propeller motor during operation, which modifies the corresponding noise that is produced and reduces stresses on the various components. The floating portion is surrounded on all sides by isolation portions (e.g., made of elastomers or other materials) that are held within a casing that attaches to the body of the UAV. In one implementation, the motor mount assembly is modular such that one or more of the isolation portions may be replaced with different isolation portions (e.g., having different attenuation properties), depending on the direction and nature of the vibrations from the propeller motor that are to be attenuated for a particular application.

Abstract: An aerial vehicle may be equipped with propellers having reconfigurable geometries. Such propellers may have blade tips or other features that may be adjusted or reconfigured while the aerial vehicle is operating, on any basis. Propellers having reconfigurable blade tips joined to blade roots may cause the blade tips to be aligned with the blade roots, or substantially perpendicular to the blade roots, e.g., in order to counter adverse effects of tip vortices, or at any intervening angle. The propellers may be reconfigured at predetermined times during operation of an aerial vehicle, or upon sensing one or more operational characteristics or environmental conditions, as may be desired or required.

Abstract: This disclosure describes an unmanned aerial vehicle (“UAV”) configured to autonomously deliver items of inventory to various destinations. The UAV may receive inventory information and a destination location and autonomously retrieve the inventory from a location within a materials handling facility, compute a route from the materials handling facility to a destination and travel to the destination to deliver the inventory.

Abstract: A package delivery system can be implemented to forcefully propel a package from an unmanned aerial vehicle (UAV), while the UAV is in motion. The UAV can apply a force onto the package that alters its descent trajectory from a parabolic path to a vertical descent path. The package delivery system can apply the force onto the package in a number of different ways. For example, pneumatic actuators, electromagnets, spring coils, and parachutes can generate the force that establishes the vertical descent path of the package. Further, the package delivery system can also monitor the package during its vertical descent. The package can be equipped with one or more control surfaces. Instructions can be transmitted from the UAV via an RF module that cause the one or more controls surfaces to alter the vertical descent path of the package to avoid obstructions or to regain a stable orientation.

Abstract: This disclosure describes a system and method for operating an automated aerial vehicle wherein the battery life may be extended by performing one or more electricity generation procedures on the way to a destination (e.g., a delivery location for an item). In various implementations, the electricity generation procedure may include utilizing an airflow to rotate one or more of the propellers of the automated aerial vehicle so that the associated propeller motors will generate electricity (e.g., which can be utilized to recharge the battery, power one or more sensors of the automated aerial vehicle, etc.). In various implementations, the airflow may consist of a wind, or may be created by the kinetic energy of the automated aerial vehicle as it moves through the air (e.g., as part of a normal flight path and/or as part of an aerial maneuver).

Abstract: This disclosure is directed to an unmanned aerial vehicle (“UAV”) that transitions in-flight between vertical flight configuration and horizontal flight configuration by changing an orientation of the UAV by approximately ninety degrees. The UAV may include propulsion units that are coupled to a wing. The wing may include wing segments rotatably coupled together by pivots that rotate to position the propulsion units around a center of mass of the UAV when the fuselage is oriented perpendicular with the horizon. In this vertical flight configuration, the UAV may perform vertical flight or hover. During the vertical flight, the UAV may cause the wing to extend outward via the pivots such that the wing segments become positioned substantially parallel to one another and the wing resembles a conventional fixed wing. With the wing extended, the UAV assumes a horizontal flight configuration that provides upward lift generated from the wing.

Abstract: This disclosure describes a system and method for determining the center of gravity of a payload engaged by an automated aerial vehicle and adjusting components of the automated aerial vehicle and/or the engagement location with the payload so that the center of gravity of the payload is within a defined position with respect to the center of gravity of the automated aerial vehicle. Adjusting the center of gravity to be within a defined position improves the efficiency, maneuverability and safety of the automated aerial vehicle. In some implementations, the stability of the payload may also be determined to ensure that the center of gravity does not change or shift during transport due to movement of an item of the payload.

Abstract: Noises that are to be emitted by an aerial vehicle during operations may be predicted using one or more machine learning systems, algorithms or techniques. Anti-noises having equal or similar intensities and equal but out-of-phase frequencies may be identified and generated based on the predicted noises, thereby reducing or eliminating the net effect of the noises. The machine learning systems, algorithms or techniques used to predict such noises may be trained using emitted sound pressure levels observed during prior operations of aerial vehicles, as well as environmental conditions, operational characteristics of the aerial vehicles or locations of the aerial vehicles during such prior operations. Anti-noises may be identified and generated based on an overall sound profile of the aerial vehicle, or on individual sounds emitted by the aerial vehicle by discrete sources.