Qualcomm Incorporated

Travis Van Schoyck

Daniel Warren Mellinger, Iii

Michael Joshua Shomin

Jonathan Paul Davis

Ross Eric Kessler

Stephen Marc Chaves

Aleksandr Kushleyev

John Anthony Dougherty

Michael Franco Taveira

Paul Daniel Martin

Matthew Hyatt Turpin

Rizwan Ehtesham Ahmed

Moussa Ben Coulibaly

Donald Hutson

Charles Wheeler Sweet, Iii

Kristen Wagner Cerase

Clayton Dumstorff

Paul Ferrell

Daniel Warren Mellinger Iii

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.

Systems and methods for automatically customizing operation of a robotic vehicle

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.

Intelligent and adaptive traffic control system

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.

Managing cleaning robot behavior

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.).

Robotic stair lifts

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.

Interference mitigation in magnetometers

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. Some embodiments may include identifying a current operator, retrieving an operator profile and associated metadata for the operator from a central database, configuring the robotic vehicle based on preference-based and performance-based settings, analyzing input data during operation, storing identified real-time operator habit information during operation of the robotic vehicle, deriving updated preference-based and performance-based settings for the operator; and uploading to the central database modifications to the metadata associated with the operator profile of the operator.

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.

Collision management for a robotic vehicle

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.

Systems and methods for improving performance of a robotic vehicle by managing on-board camera defects

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.

Pressure tap structures for barometric altimeters for unmanned aerial vehicles

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.

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Lafayette Hill, PA, United States of America

Travis Van Schoyck