Abstract: Embodiments include devices and methods for managing network communication of an unmanned autonomous vehicle (UAV). A processor of the UAV may determine an altitude of the UAV. The processor may optionally also determine a speed or vector of the UAV. Based on the determined altitude and/or speed/vector of the UAV, the processor may adjust the communication parameter of the communication link between the UAV and a communication network. The processor may transmit signals based on the adjusted communication parameter, which may reduce radio frequency interference caused by the transmissions of the UAV with the communication network.

Abstract: Methods and apparatuses are disclosed for determining a characteristic of a device's object detection sensor oriented in a first direction. An example device may include one or more processors. The device may further include a memory coupled to the one or more processors, the memory including one or more instructions that when executed by the one or more processors cause the device to determine a direction of travel for the device, compare the direction of travel to the first direction to determine a magnitude of difference, and determine a characteristic of the object detection sensor based on the magnitude of difference.

Abstract: Embodiments include devices and methods for managing network communication of an unmanned autonomous vehicle (UAV). A processor of the UAV may determine an altitude of the UAV. The processor may optionally also determine a speed or vector of the UAV. Based on the determined altitude and/or speed/vector of the UAV, the processor may adjust the communication parameter of the communication link between the UAV and a communication network. The processor may transmit signals based on the adjusted communication parameter, which may reduce radio frequency interference caused by the transmissions of the UAV with the communication network.

Abstract: Methods and apparatuses are disclosed for determining a characteristic of a device's object detection sensor oriented in a first direction. An example device may include one or more processors. The device may further include a memory coupled to the one or more processors, the memory including one or more instructions that when executed by the one or more processors cause the device to determine a direction of travel for the device, compare the direction of travel to the first direction to determine a magnitude of difference, and determine a characteristic of the object detection sensor based on the magnitude of difference.

Abstract: Embodiments include devices and methods for managing network communication of an unmanned autonomous vehicle (UAV). A processor of the UAV may determine an altitude of the UAV. The processor may optionally also determine a speed or vector of the UAV. Based on the determined altitude and/or speed/vector of the UAV, the processor may adjust the communication parameter of the communication link between the UAV and a communication network. The processor may transmit signals based on the adjusted communication parameter, which may reduce radio frequency interference caused by the transmissions of the UAV with the communication network.

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 a drone having a landing control device that is configured to rotate wings into an auto-rotation decent configuration causing the drone to enter a nose-down attitude and spin about a long axis of the drone, and to collectively control pivot angles of the wings to enables control of decent rate and lateral motion during an auto-rotation descent. The landing control device may be a landing carousel including a pivotal frame secured to a drone body and configured to rotate about a carousel axis extending laterally relative to a longitudinal axis of the body. The landing carousel may include a first wing motor configured to pivot a first wing about a wing pivot axis extending parallel to the carousel axis, and a second wing motor configured to pivot a second wing about the wing pivot axis independent of the pivot the first wing.

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: Various embodiments include methods that may be implemented in a processor or processing device of an aerial robotic vehicle for generating three-dimensional terrain map based on the plurality of altitude above ground level values generated using visual-inertial odometry, and using such terrain maps to control the altitude of the aerial robotic vehicle. Some methods may include using the generated three-dimensional terrain map during landing. Such embodiment may further include refining the three-dimensional terrain map using visual-inertial odometry as the vehicle approaches the ground and using the refined terrain maps during landing. Some embodiments may include using the three-dimensional terrain map to select a landing site for the vehicle.

Abstract: Various embodiments include a drone having a landing control device that is configured to rotate wings into an auto-rotation decent configuration causing the drone to enter a nose-down attitude and spin about a long axis of the drone, and to collectively control pivot angles of the wings to enables control of decent rate and lateral motion during an auto-rotation descent. The landing control device may be a landing carousel including a pivotal frame secured to a drone body and configured to rotate about a carousel axis extending laterally relative to a longitudinal axis of the body. The landing carousel may include a first wing motor configured to pivot a first wing about a wing pivot axis extending parallel to the carousel axis, and a second wing motor configured to pivot a second wing about the wing pivot axis independent of the pivot the first wing.

Abstract: Embodiments of the invention disclose methods, apparatuses, systems, and computer-readable media for taking and sharing pictures of objects of interest at an event or an occasion. A device implementing embodiments of the invention may enable a user to select objects of interest from a view displayed by a display unit coupled to the device. The device may also have pre-programmed objects including objects that the device detects. In addition, the device may detect people using the users' social networks by retrieving images from social networks like Facebook® and LinkedIn®.

Abstract: Various systems and methods of dynamically filtering depth estimates to generate a volumetric map of a three-dimensional (3-D) environment having an adjustable maximum depth include obtaining sensor output including depth estimates and pose estimates in a robotic vehicle, detecting a condition that corresponds to an error level in the pose estimates, filtering the depth estimates obtained from the sensor output based on the detected condition, and generating the volumetric map of the 3-D environment using the filtered depth estimates. Filtering depth estimates obtained from the sensor output based on the detected condition may include adjusting a maximum depth parameter for generating the volumetric map. Further embodiments include a robotic vehicle and/or a computing device within a robotic vehicle including a processor configured with processor-executable instructions for controlling the maximum depth of a volumetric map of a 3-D environment.

Abstract: Various arrangements for tracking a target within a series of images is presented. The target may be detected within a first image at least partially based on a correspondence between the target and a stored reference template. A tracking template may be created for tracking the target using the first image. The target may be located within a second image using the tracking template.

Abstract: Various embodiments involve dynamically controlling parameters for processing sensor data, including rates at which vehicle sensors are sampled and analyzed, based on the vehicle's speed and direction. Data or sampling rates of sensors useful for collision avoidance and/or path planning may be adjusted to emphasize data from sensors having a field of view encompassing the travel direction, while limiting processing of data from sensors less likely to provide useful data for such purposes. In some embodiments, the rate at which data from a particular sensor is sampled and/or processed may depend on a vehicle's direction and speed of travel as well as the sensor's field of view. Processing demands may be reduced by focusing processing on data from sensors viewing the direction of travel while reducing processing of data from sensors viewing other directions. In some embodiments, sensor data sampling or processing rates may vary based on collision risk probabilities.

Abstract: Methods and apparatuses are disclosed for determining a characteristic of a device's object detection sensor oriented in a first direction. An example device may include one or more processors. The device may further include a memory coupled to the one or more processors, the memory including one or more instructions that when executed by the one or more processors cause the device to determine a direction of travel for the device, compare the direction of travel to the first direction to determine a magnitude of difference, and determine a characteristic of the object detection sensor based on the magnitude of difference.

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: Embodiments of the invention disclose methods, apparatuses, systems, and computer-readable media for taking and sharing pictures of objects of interest at an event or an occasion. A device implementing embodiments of the invention may enable a user to select objects of interest from a view displayed by a display unit coupled to the device. The device may also have pre-programmed objects including objects that the device detects. In addition, the device may detect people using the users' social networks by retrieving images from social networks like Facebook® and LinkedIn®.

Abstract: Apparatuses and methods for detecting an obstacle in a path of an Unmanned Aerial Vehicle (UAV) are described herein, including, but not limited to, receiving data from a single image/video capturing device of the UAV, computing a score based on the received data, and performing at least one obstacle avoidance maneuver based on the score.

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.

Abstract: Various embodiments include dynamically controlling one or more parameters for obtaining and/or processing sensor data received from a sensor on a vehicle based on the speed of the vehicle. In some embodiments, parameters for obtaining and/or processing sensor data may be individually tuned (e.g., decreased, increased, or maintained) by leveraging differences in the level of quality, accuracy, confidence and/or other criteria in sensor data associated with particular missions/tasks performed using the sensor data. For example, the sensor data resolution required for collision avoidance may be less than the sensor data resolution required for inspection tasks, while the update rate required for inspection tasks may be less than the update rate required for collision avoidance. Parameters for obtaining and/or processing sensor data may be individually tuned based on the speed of the vehicle and/or the task or mission to improve consumption of power and/or other resources.