Abstract: Methods, systems, and devices for automatically customizing operation of a robotic vehicle are described. The method may include identifying an operator, retrieving an operator profile and associated metadata for the operator from a database, where the metadata includes operator habit information, and configuring the robotic vehicle based on existing preference-based and performance-based settings, where the existing preference-based and performance-based settings are based on the metadata. The methods may include identifying operator habit information during operation of the robotic vehicle, deriving updated preference-based and performance-based settings for the operator based on the identified operator habit information, and providing, to the database, modifications to the metadata associated with the operator profile of the operator.

Abstract: Various embodiments include methods and interactive traffic control devices for interactively controlling traffic, which may include receiving refined location and state information associated with individual vehicles on a roadway, and determining customized dynamic traffic control instructions for a first one or more of the individual vehicles. The determined customized dynamic traffic control instructions may be based on the received refined location and state information and offer an optional route alternative to a set limited number of the individual vehicles. The first customized dynamic traffic control instructions may be transmitted by the interactive traffic control device to the first one or more of the individual vehicles.

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: Methods, systems, and devices for robotic navigation are described. A robotic device such as a robotic vacuum or a robotic assistant may navigate a first surface. In some cases, navigating the first surface may include removing debris from the first surface. The robotic device may identify a location of a track that connects the first surface to a second surface that is vertically displaced from the first surface. The robotic device may engage the track based at least in part on the identified location. The robotic device may ascend to the second surface by activating an actuator and navigate the second surface (e.g., may remove debris from the second surface, may map the second surface, etc.).

Abstract: Methods, systems, and devices for automatically customizing operation of a robotic vehicle are described. The method may include identifying an operator, retrieving an operator profile and associated metadata for the operator from a database, where the metadata includes operator habit information, and configuring the robotic vehicle based on existing preference-based and performance-based settings, where the existing preference-based and performance-based settings are based on the metadata. The methods may include identifying operator habit information during operation of the robotic vehicle, deriving updated preference-based and performance-based settings for the operator based on the identified operator habit information, and providing, to the database, modifications to the metadata associated with the operator profile of the operator.

Abstract: Various embodiments include devices and methods for mitigating the bias of a magnetometer resulting from operating various hardware components on a device such as a drone or a computing device. Various embodiments may improve the accuracy of magnetometer output by estimating the bias or magnetic interference caused by the hardware components based on a utilization or operating state of each hardware component, and adjusting the magnetometer output to compensate for the estimated bias.

Abstract: Some embodiments include methods for customizing operation of the robotic vehicle for an operator. Such embodiments may include identifying a current operator of the robotic vehicle, configuring the robotic vehicle based on metadata associated with an operator profile for the operator, determining whether the operator has changed, and if so, identifying the new operator, deriving updated preference-based settings and performance-based settings for the new operator, and updating configurations of the robotic vehicle accordingly.

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: 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 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 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 methods, systems, and devices for interactively controlling traffic. The method, which may be performed by operations of the systems and/or devices, may include receiving, for example by an interactive traffic control device, refined location and state information associated with a first vehicle on a roadway. The interactive traffic control device may also determine at least one notable element in the refined location and state information, customized dynamic traffic control instructions based on the refined location and state information, and whether the customized dynamic traffic control instructions conflict with the at least one notable element. In addition, the interactive traffic control device may transmit the customized dynamic traffic control instructions to the first vehicle in response to determining the customized dynamic traffic control instructions do not conflict with the at least one notable element.

Abstract: Various embodiments include methods and interactive traffic control devices for interactively controlling traffic, which may include receiving refined location and state information associated with individual vehicles on a roadway, and determining customized dynamic traffic control instructions for a first one or more of the individual vehicles. The determined customized dynamic traffic control instructions may be based on the received refined location and state information and offer an optional route alternative to a set limited number of the individual vehicles. The first customized dynamic traffic control instructions may be transmitted by the interactive traffic control device to the first one or more of the individual vehicles.

Abstract: Various embodiments may include methods of limiting a steering command angle during operation of a vehicle. Various embodiments may include determining a speed of the vehicle, applying the determined speed to a dynamic model of the autonomous vehicle to determine a steering wheel command angle limit. Embodiments may further include determining whether a received or commanded steering command angle exceeds the steering wheel command angle limit and altering the steering command angle to an angle no greater than the maximum steering command angle if the received/commanded steering command angle exceeds the steering wheel command angle limit.

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: 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 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: Methods, systems, and devices for debris permutation are described. A robotic device may identify a cleaning trigger for a first surface region (e.g., a cleaning schedule, a notification from a remote device). The robotic device may activate one or more rotors o based at least in part on the surface cleaning trigger and move to an aerial position proximal to (e.g., above, diagonal to) the first surface region using the one or more rotors. The device may displace debris from the first surface region to a second surface region using a pressurized air stream.

Abstract: Methods, systems, and devices for robotic navigation are described. A robotic device such as a robotic vacuum or a robotic assistant may navigate a first surface. In some cases, navigating the first surface may include removing debris from the first surface. The robotic device may identify a location of a track that connects the first surface to a second surface that is vertically displaced from the first surface. The robotic device may engage the track based at least in part on the identified location. The robotic device may ascend to the second surface by activating an actuator and navigate the second surface (e.g., may remove debris from the second surface, may map the second surface, etc.).