Abstract: Various embodiments include methods and interactive traffic control devices implementing such methods to receive refined location and state information associated with individual vehicles and determine first customized dynamic traffic control instructions for a first one or more of the individual vehicles and second customized dynamic traffic control instructions for a second one or more of the individual vehicles different from the first one or more of the individual vehicles. The first customized dynamic traffic control instructions may be transmitted to the first one or more of the individual vehicles, and the second customized dynamic traffic control instructions may be transmitted to the second one or more of the individual vehicles.

Abstract: Various embodiments include processing devices and methods for managing cleaning robot behavior. In some embodiments, a processor of the cleaning robot may obtain information about one or more cleaning operations in one or more locations of a structure. The processor may analyze the information about the one or more cleaning operations in the one or more locations. The processor may determine one or more cleaning parameters for the cleaning robot based on the analysis of the information about the one or more cleaning operations. Processor may generate an instruction for the cleaning robot to schedule an operation of the cleaning robot based on the one or more cleaning parameters. The processor may execute the generated instruction to perform the operation of the cleaning robot.

Abstract: Various embodiments include processing devices and methods for managing cleaning robot behavior. In some embodiments, a processor of the cleaning robot may obtain one or more images of the location of a structure from a camera external to the cleaning robot. The processor may analyze the one or more images of the location. The processor may determine one or more mess parameters of a mess in the location based on the analysis of the one or more images of the location. The processor may generate an instruction for the cleaning robot to schedule an operation of the cleaning robot based on the one or more mess parameters. The processor may execute the generated instruction to perform the operation of the cleaning robot.

Abstract: Various embodiments include processing devices and methods for managing cleaning behavior by a cleaning robot. In some embodiments, a processor of the cleaning robot may obtain user planning information and user location information from one or more information sources external to the cleaning robot. The processor may analyze the user planning information and the user location information. The processor may determine one or more cleaning parameters for the cleaning robot based on the analysis of the user planning information and the user location information. The processor may generate an instruction for the cleaning robot to schedule an operation of the cleaning robot based on the one or more cleaning parameters. The processor may execute the generated instruction to perform the operation of the cleaning robot.

Abstract: Various embodiments include processing devices and methods for managing cleaning robot behavior. In some embodiments, a processor of the cleaning robot may obtain one or more images of the location of a structure from a camera external to the cleaning robot. The processor may analyze the one or more images of the location. The processor may determine one or more activity parameters of the location based on the analysis of the one or more images of the location. The processor may generate an instruction for the cleaning robot to schedule an operation of the cleaning robot based on the one or more activity parameters. The processor may execute the generated instruction to perform the operation of the cleaning robot.

Abstract: Various embodiments include processing devices and methods for managing cleaning robot behavior. In some embodiments, a processor of the cleaning robot may determine operational information about operations of a heating, ventilation, and air conditioning (HVAC) system for at least one room in a structure. The processor may determine a time when operation of the HVAC system will end based on the determined operational information. The processor may generate an instruction for the cleaning robot to schedule an operation of the cleaning robot for a time after operation of the HVAC system will end. The processor may execute the generated instruction to perform the operation of the cleaning robot after operation of the HVAC system ends.

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: A lighting system for an unmanned autonomous vehicle (UAV) adapts to the environment around the UAV to ensure status notification lights are visible to an operator and/or abide by regulatory lighting requirements. A processor of the UAV may receive information from various sensors regarding environmental conditions and location of the UAV, and adjust a UAV lighting system to ensure visibility under the environmental conditions. Adjustments to the lighting system may include selection of light sources that are illuminated, the illumination intensity of particular light sources, the colors emitted by various light sources and other lighting configurations.

Abstract: Various embodiments include devices and methods for navigating a robotic vehicle within an environment. In various embodiments, a first image frame is captured using a first exposure setting and a second image frame is captured using a second exposure setting. A plurality of points may be identified from the first image frame and the second image frame. A first visual tracker may be assigned to a first set of the plurality of points and a second visual tracker may be assigned to a second set of the plurality of points. Navigational data may be generated based on results of the first visual tracker and the second visual tracker. The robotic vehicle may be controlled to navigate within the environment using the navigation data.

Abstract: A charging station for a robotic vehicle includes a base configured for use on a body of water; a docking terminal supported on the base, the docking terminal including a charger configured to charge a robotic vehicle docked on the docking terminal; and a renewable energy harvesting device coupled to the charger to provide power to the charger.

Abstract: Various embodiments include methods for rotor anomaly detection and response for an aerial robotic vehicle. A processor of the aerial robotic vehicle may obtain data from a sensor onboard the aerial robotic vehicle configured to detect anomalies in rotors. The processor may determine whether an anomaly is detected in any rotor based on the obtained data and take an action in response to detecting an anomaly in one or more rotors. Examples of actions that may be taken in response to detecting a rotor anomaly include preventing the aerial robotic vehicle from lifting-off, limiting operations of the aerial robotic vehicle within certain performance limits, and issuing a maintenance alert by the processor.

Abstract: Embodiments include devices and methods operating a robotic vehicle. A robotic vehicle processor may detect an object posing an imminent risk of collision with the robotic vehicle. The robotic vehicle processor may determine a classification of the detected object. The robotic vehicle processor may manage a rotation of a rotor of the robotic vehicle prior to a collision based on the classification of the object.

Abstract: Embodiments include methods performed by a processor of a robotic vehicle for detecting and responding to obstructions to an on-board imaging device that includes an image sensor. Various embodiments may include causing the imaging device to capture at least one image, determining whether an obstruction to the imaging device is detected based at least in part on the at least one captured image, and, in response to determining that an obstruction to the imaging device is detected, identifying an area of the image sensor corresponding to the obstruction and masking image data received from the identified area of the image sensor.

Abstract: Embodiments include methods performed by a processor of a robotic vehicle for detecting and responding to defects on an on-board imaging device that includes an image sensor. Various embodiments may include causing the imaging device to capture at least one image, determining whether a defect to the imaging device is detected based at least in part on the at least one captured image, and, in response to determining that a defect to the imaging device is detected, identifying an area of the image sensor corresponding to the defect and masking image data received from the identified area of the image sensor.

Abstract: Various embodiments include methods, devices, and systems of securely delivering an item using a robotic vehicle and a security device that renders the item unusable without authorized removal there from or deactivation of the security device. The robotic vehicle may include a payload securing unit and a robotic vehicle processor. The payload securing unit may be configured to selectively hold the item or the security device while the item is secured to the security device. The robotic vehicle processor may be configured with processor-executable instructions to transport the item to the delivery destination while held by the payload securing unit and secured to the security device. The robotic vehicle may depart the delivery destination prior to receiving authorization to depart relating to the item.

Abstract: Compositions and methods are disclosed for altering the binding affinity of calmodulin for ryanodine receptor 2 (RyR2). As disclosed herein, these therapeutic calmodulin (TCaM) proteins can be used to correct ryanopathies by prolonging the RyR2 refractory period. Therefore, also disclosed is a method for treating a ryanopathy-associated disease in a subject that involves administering to the subject a composition comprising a TCaM disclosed herein.

Abstract: A lighting system for an unmanned autonomous vehicle (UAV) adapts to the environment around the UAV to ensure status notification lights are visible to an operator and/or abide by regulatory lighting requirements. A processor of the UAV may receive information from various sensors regarding environmental conditions and location of the UAV, and adjust a UAV lighting system to ensure visibility under the environmental conditions. Adjustments to the lighting system may include selection of light sources that are illuminated, the illumination intensity of particular light sources, the colors emitted by various light sources and other lighting configurations.

Abstract: Methods, devices, and systems of various embodiments are disclosed for operating a propeller assembly for use with a UAV. Various embodiments include a propeller assembly including a pivotal arm, a propeller mounted on the pivotal arm, and pivotal leg coupled to the pivotal arm. The pivotal leg may be folded into the pivotal arm and the pivotal arm may be folded into a body of the UAV. A processor may be coupled to the propeller assembly and configured with processor-executable instructions to perform operations of the propeller assembly.

Abstract: Various embodiments include a structure configured to at least partially expose a barometric altimeter of an unmanned aerial vehicle (UAV) to air pressure at a location on the UAV where there is reduced pressure perturbations caused by downwash of propellers. The structure may include a proximal portion configured to encompass a barometric altimeter of a circuit board of the UAV. The proximal portion may form at least a partial barrier between the barometric altimeter and a first ambient air pressure that is disturbed by a downwash from propellers of the UAV during flight of the UAV. The structure may also include a distal portion extending away from the barometric altimeter, with the distal portion configured to channel to the barometric altimeter a second ambient air pressure that is disturbed less than the first ambient air pressure by the downwash from propellers of the UAV during flight of the UAV.

Abstract: Embodiments described herein relates to an Unmanned Aerial Vehicle (UAV) having vibration dampening and isolation capabilities, the UAV including a first frame portion, a second frame portion, and a third frame portion. Each of the first frame portion, the second frame portion, and the third frame portion is separated from one another. At least one first support member inelastically coupling the first frame portion and the third frame portion. At least one second support member elastically coupling the second frame portion and one or more of the first frame portion or the third frame portion to isolate the first frame portion and the third frame portion from vibration of the second frame portion.