Abstract: Various methods for monitoring a target user by a robotic vehicle include tracking the target user by the robotic vehicle, detecting an object in the presence of the target user based on one or more detection criteria, determining whether the object is a potential threat to the target user based on one or more threat criteria, determining whether to notify the third party of the potential threat to the target user based on one or more notification criteria in response to determining that the object is a potential threat, and notifying the third party of the potential threat to the target user in response to determining that the third party should be notified.

Abstract: Various methods for monitoring a target user by a drone include tracking the target user by the drone, detecting an object in the presence of the target user based on one or more detection criteria, determining whether the object is a potential threat to the target user based on one or more threat criteria, determining whether to notify the third party of the potential threat to the target user based on one or more notification criteria in response to determining that the object is a potential threat, notifying the third party of the potential threat to the target user in response to determining that the third party should be notified, receiving a response from the third party including a command, and performing an action based on the command.

Abstract: Various embodiments include methods, devices, and robotic vehicle processing devices implementing such methods for automatically adjusting the minimum distance that a robotic vehicle is permitted to approach an object by a collision avoidance system (the “proximity threshold”) to compensate for unpredictability in environmental or other conditions that may compromise control or navigation of the robotic vehicle, and/or to accommodate movement unpredictability of the object. Some embodiments enable dynamic adjustments to the proximity threshold to compensate for changes in environmental and other conditions. Some embodiments include path planning that takes into account unpredictability in environmental or other conditions plus movement unpredictability of objects in the environment.

Abstract: Various embodiments include methods, devices, and robotic vehicles that adjust a proximity threshold implemented in a collision avoidance system based on whether a payload is being carried. Methods may include determining whether a payload is carried by the robotic vehicle, setting a proximity threshold for collision avoidance in response to determining that a payload is carried by the robotic vehicle, and controlling one or more motors of the robotic vehicle using the proximity threshold for collision avoidance. Some embodiments may include raising the proximity threshold when a payload is not being carried or decreasing proximity threshold when a payload is being carried. Some embodiments may include determining a classification of a payload and setting the proximity threshold based at least in part on the classification.

Abstract: Various embodiments include methods, devices, and robotic vehicle processing devices implementing such methods for automatically adjusting the minimum distance that a robotic vehicle is permitted to approach an object by a collision avoidance system based upon a classification or type of object.

Abstract: Various embodiments include methods and aerial robotic vehicles that adjust a flight control parameter based on whether propeller guards are installed. An aerial robotic vehicle processor may determine whether a propeller guard is installed, set a flight parameter based on the determination, and control one or more motors of the aerial robotic vehicle using the flight parameter. When propeller guards are installed, the flight parameter may be set to a value appropriate for controlling the aerial robotic vehicle when the propeller guard is installed. The flight parameter may be one or more of control gains, drag profile control settings, a maximum rotor speed, maximum speed of the aerial robotic vehicle, maximum power usage, restrictions to select modes of operation, visual algorithm settings, or a flight plan. Data from one or more sensors and/or motor controllers may be used to determine the presence of a propeller guard.

Abstract: Methods, systems, and devices are disclosed for operating a drone consistent with an access level of the drone and/or an operator of the drone. Various embodiments may include determining, by a processor of the drone, whether the drone is registered with an agency or the operator of the drone is registered to operate the drone. In response to determining that the drone and/or the operator is registered, the drone processor may operate the drone consistent with an access level of the drone and/or operator. In response to determining that the drone and/or the operator is registered, the drone processor may restrict operations of the drone.

Abstract: Methods, systems, and devices for performing autonomous self-service are described. A robotic device may identify a status of a chamber associated with the robotic device based on sensor data received from a sensor of the robotic device and pause an autonomous debris collection process of the robotic device based on the identified status. The robotic device may automatically remove a first container from the chamber based on the identified status and discard the first container away from the robotic device. In some examples, the robotic device may discard the first container at a fixed position within a geo-boundary corresponding to the debris collection process. The robotic device may resume the autonomous debris collection process based on an introduction of a second container.

Abstract: Various methods enable a processor of a robotic vehicle to determine when the robotic vehicle has been stolen so that a self-recovery operation may be performed. Determining whether the robotic vehicle has been stolen may include evaluating, by a processor of the robotic vehicle, unauthorized use indicia, and determining that the robotic vehicle is stolen in response to determining that unauthorized use indicia exceed a threshold. Evaluating unauthorized use indicia may include determining whether an Integrated Circuit Card Identifier of a Subscriber Identify Module matches a stored value, determining whether a paired controller is different from a usual controller, determining whether the operator's skill has changed, and evaluating one or more trust factors that are observable features of normal operation.

Abstract: Various methods enable a robotic vehicle to determine that it has been stolen, determine an appropriate opportunity to perform a recovery operation, and perform the recovery operation at the appropriate opportunity. Examples of recovery operations include traveling to a predetermined location, identifying and traveling to a “safe” location to await recovery, and crashing to self-destruct when the predetermined location cannot be reached and a “safe” location cannot be identified.

Abstract: Various embodiments enable recovery with a robotic vehicle of an item placed by a user on a delivery pad. The presence of the item on the delivery pad may be sensed and various descriptive recovery parameters may be included in a recovery request. Recovery parameters may be derived from measurements acquired at the delivery pad, information stored in the user account, and information input by a user using an application executing on a user device. The application may be associated with the user account. The recovery request may be sent to a remote server which in turn dispatches a robotic vehicle to the delivery pad site to recover the item and routes the robotic vehicle with the recovered item to a location based on information in the user account. A robotic vehicle selection may be based on the item's weight or one or more of its physical dimensions.

Abstract: Various embodiments enable recovery with a robotic vehicle of an item placed by a user in a delivery area. The presence of the item in the delivery area may be determined using images captured by a camera, with descriptive recovery parameters derived and included in a recovery request. Recovery parameters may also include information stored in a user account and information input by a user using an application executing on a user device. The delivery area and application may be associated with the user account. The recovery request may be sent to a remote server which dispatches a robotic vehicle to the delivery area to recover the item and routes the robotic vehicle with the recovered item to a location based on information in the user account. A selection of robotic vehicle type may be based on the item's weight or one or more of its physical dimensions.

Abstract: Various embodiments include methods and aerial robotic vehicles that adjust a flight control parameter based on whether propeller guards are installed. An aerial robotic vehicle processor may determine whether a propeller guard is installed, set a flight parameter based on the determination, and control one or more motors of the aerial robotic vehicle using the flight parameter. When propeller guards are installed, the flight parameter may be set to a value appropriate for controlling the aerial robotic vehicle when the propeller guard is installed. The flight parameter may be one or more of control gains, drag profile control settings, a maximum rotor speed, maximum speed of the aerial robotic vehicle, maximum power usage, restrictions to select modes of operation, visual algorithm settings, or a flight plan. Data from one or more sensors and/or motor controllers may be used to determine the presence of a propeller guard.

Abstract: Various embodiments include methods, devices, and robotic vehicle processing devices implementing such methods for automatically adjusting the minimum distance that a robotic vehicle is permitted to approach an object by a collision avoidance system based upon a classification or type of object.

Abstract: Various embodiments include methods, devices, and robotic vehicles that adjust a proximity threshold implemented in a collision avoidance system based on whether a payload is being carried. Methods may include determining whether a payload is carried by the robotic vehicle, setting a proximity threshold for collision avoidance in response to determining that a payload is carried by the robotic vehicle, and controlling one or more motors of the robotic vehicle using the proximity threshold for collision avoidance. Some embodiments may include raising the proximity threshold when a payload is not being carried or decreasing proximity threshold when a payload is being carried. Some embodiments may include determining a classification of a payload and setting the proximity threshold based at least in part on the classification.

Abstract: Various embodiments include methods, devices, and aerial robotic vehicles for adjusting a proximity threshold implemented in a collision avoidance system based on whether propeller guards are installed. Methods may include an aerial robotic vehicle processor determining whether a propeller guard is installed, setting, a proximity threshold for collision avoidance based on the determination as to whether propeller guard(s) is/are installed on the aerial robotic vehicle, and controlling one or more motors of the aerial robotic vehicle using the proximity threshold for collision avoidance. When propeller guards are installed, the proximity threshold may be set at a smaller distance than when propeller guards are not installed. The determination of whether a propeller guard is installed may be based on sensor data from one or more sensors configured to detect or indicate the presence of a propeller guard, and/or based on rotor revolution rates determined from a motor or motor controller.

Abstract: Various embodiments include methods, devices, and robotic vehicle processing devices implementing such methods for automatically adjusting the minimum distance that a robotic vehicle is permitted to approach an object by a collision avoidance system (the “proximity threshold”) to compensate for unpredictability in environmental or other conditions that may compromise control or navigation of the robotic vehicle, and/or to accommodate movement unpredictability of the object. Some embodiments enable dynamic adjustments to the proximity threshold to compensate for changes in environmental and other conditions. Some embodiments include path planning that takes into account unpredictability in environmental or other conditions plus movement unpredictability of objects in the environment.

Abstract: Various methods for performing package deliveries by a robotic vehicle may include determining whether an individual at a package delivery location is a requester or an authorized recipient of a package to be delivered by the robotic vehicle at the package delivery location, sending a notification to the requester of the package in response to determining that the individual at the package delivery location is not the requester or an authorized recipient, and delivering the package to the individual at the package delivery location in response to receiving authorization from the requester to deliver the package to the individual.

Abstract: Embodiments include devices and methods for managing operation of a robotic vehicle. A robotic vehicle processor may receive supplemental delivery information from an Internet of Things (IoT) device of a delivery area. The robotic vehicle processor may determine a specific delivery location within the delivery area based on the supplemental delivery information. The robotic vehicle processor may maneuver the robotic vehicle to the specific delivery location to deliver a package at the specific delivery location.

Abstract: Methods, systems, and devices are disclosed for providing conditional access for a drone for accessing a restricted area. Conditional access information associated with conditional access restrictions for the restricted area may be received by the drone. The drone may compare the received conditional access information to one or more access parameters for the drone. The drone may access the restricted area based on the comparison of the received conditional access information and the access parameter. A drone may take corrective action when the received conditional access information does not permit access to the restricted area based on the access parameter for the drone.