Abstract: An actuator is introduced that utilizes the forces that result from placing a current carrying coil in a magnetic field to rotate a connected object about at least one axis. In some embodiments, the introduced coil actuator includes a coil of conductor coupled to an arm or other type of structural element that extends radially from an axis of rotation. The introduced coil actuator can be utilized to provide motion control in a variety of different applications such as gimbal mechanisms. In some embodiments, the introduced coil actuator can be implemented in a gimbal mechanism for adjusting an orientation of a device such as a camera relative to a connected platform such as the body of an aerial vehicle.

Abstract: A technique is introduced for autonomous landing by an aerial vehicle. In some embodiments, the introduced technique includes processing a sensor data such as images captured by onboard cameras to generate a ground map comprising multiple cells. A suitable footprint, comprising a subset of the multiple cells in the ground map that satisfy one or more landing criteria, is selected and control commands are generated to cause the aerial vehicle to autonomously land on an area corresponding to the footprint. In some embodiments, the introduced technique involves a geometric smart landing process to select a relatively flat area on the ground for landing. In some embodiments, the introduced technique involves a semantic smart landing process where semantic information regarding detected objects is incorporated into the ground map.

Abstract: Methods and systems are described for new paradigms for user interaction with an unmanned aerial vehicle (referred to as a flying digital assistant or FDA) using a portable multifunction device (PMD) such as smart phone. In some embodiments, a user may control image capture from an FDA by adjusting the position and orientation of a PMD. In other embodiments, a user may input a touch gesture via a touch display of a PMD that corresponds with a flight path to be autonomously flown by the FDA.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: A technique is described for developing and using applications and skills with an autonomous vehicle. In an example embodiment, a development platform is provided that enables access to a developer console for developing software modules for use with an autonomous vehicle. Using the developer console, a developer user can specify instructions for causing an autonomous vehicle to perform one or more operations. For example, to control the behavior of an autonomous vehicle, the instructions can cause an executing computer system at the autonomous vehicle to generate calls to an application programming interface (API) associated with an autonomous navigation system of autonomous vehicle. Such calls to the API can be configured to adjust a parameter of a behavioral objective associated with a trajectory generation process performed by the autonomous navigation system that controls the behavior of the autonomous vehicle.

Abstract: Systems and methods are disclosed for tracking objects in a physical environment using visual sensors onboard an autonomous unmanned aerial vehicle (UAV). In certain embodiments, images of the physical environment captured by the onboard visual sensors are processed to extract semantic information about detected objects. Processing of the captured images may involve applying machine learning techniques such as a deep convolutional neural network to extract semantic cues regarding objects detected in the images. The object tracking can be utilized, for example, to facilitate autonomous navigation by the UAV or to generate and display augmentative information regarding tracked objects to users.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: An autonomous vehicle that is equipped with image capture devices can use information gathered from the image capture devices to plan a future three-dimensional (3D) trajectory through a physical environment. To this end, a technique is described for image-space based motion planning. In an embodiment, a planned 3D trajectory is projected into an image-space of an image captured by the autonomous vehicle. The planned 3D trajectory is then optimized according to a cost function derived from information (e.g., depth estimates) in the captured image. The cost function associates higher cost values with identified regions of the captured image that are associated with areas of the physical environment into which travel is risky or otherwise undesirable. The autonomous vehicle is thereby encouraged to avoid these areas while satisfying other motion planning objectives.

Abstract: A technique is introduced for autonomous landing by an aerial vehicle. In some embodiments, the introduced technique includes processing a sensor data such as images captured by onboard cameras to generate a ground map comprising multiple cells. A suitable footprint, comprising a subset of the multiple cells in the ground map that satisfy one or more landing criteria, is selected and control commands are generated to cause the aerial vehicle to autonomously land on an area corresponding to the footprint. In some embodiments, the introduced technique involves a geometric smart landing process to select a relatively flat area on the ground for landing. In some embodiments, the introduced technique involves a semantic smart landing process where semantic information regarding detected objects is incorporated into the ground map.

Abstract: In some examples, an unmanned aerial vehicle (UAV) may control a position of a first camera to cause the first camera to capture a first image of a target. The UAV may receive a plurality of second images from a plurality of second cameras, the plurality of second cameras positioned on the UAV for providing a plurality of different fields of view in a plurality of different directions around the UAV, the first camera having a longer focal length than the second cameras. The UAV may combine at least some of the plurality of second images to generate a composite image corresponding to the first image and having a wider-angle field of view than the first image. The UAV may send the first image and the composite image to a computing device.

Abstract: The technology described herein relates to autonomous aerial vehicle rotor configurations. In some embodiments, the aerial vehicle includes a central body that extends along a longitudinal axis from a forward end to an aft end including a port side opposite a starboard side. Multiple rotor arms each have a proximal end coupled to the central body and a rotor assembly arranged at a distal end to provide propulsion for the aerial vehicle. The rotor assemblies include a first set of rotor assemblies and a second set of rotor assemblies. The first set of rotor assemblies are arranged in a non-inverted configuration on a top side of the aerial vehicle such that each rotor assembly includes an upward-facing rotor. The second set of rotor assemblies are arranged in an inverted configuration on a bottom side of the aerial vehicle such that each rotor assembly includes a downward-facing rotor.

Abstract: Embodiments are described for a stabilization system configured, in some embodiments, for stabilizing image capture from an aerial vehicle (e.g., a UAV). According to some embodiments, the stabilization systems employs both active and passive stabilization means. A passive stabilization assembly includes a counter-balanced suspension system that includes an elongated arm that extends into and is coupled to the body of a vehicle. The counter-balanced suspension system passively stabilizes a mounted device such as an image capture device to counter motion of the UAV while in use. In some embodiment the counter-balanced suspension system passively stabilizes a mounted image capture assembly that includes active stabilization means (e.g., a motorized gimbal and/or electronic image stabilization). In some embodiments, the active and passive stabilization means operate together to effectively stabilize a mounted image capture device to counter a wide range of motion characteristics.

Abstract: The technology described herein relates to autonomous aerial vehicle technology and, more specifically, to environment illumination for autonomous unmanned aerial vehicles. In some embodiments, a UAV includes upward-facing image capture devices, downward-facing image capture devices, one or more illumination sources, and a computer system. The computer system is configured to direct the one or more illumination sources to selectively emit light into a surrounding physical environment while the UAV is in flight, process images captured by any one or more of the plurality of upward-facing image capture devices or the plurality of downward-facing image capture devices to estimate a position and/or orientation of the aerial vehicle, generate a planned trajectory for the aerial vehicle through a physical environment based on the processing of the images, and control a propulsion system and/or flight surface of the aerial vehicle to cause the aerial vehicle to autonomously maneuver along the planned trajectory.

Abstract: The technology described herein relates to autonomous aerial vehicle technology and, more specifically, to autonomous unmanned aerial vehicle with folding collapsible arms. In some embodiments, a UAV including a central body, a plurality of rotor arms, and a plurality of hinge mechanisms is disclosed. The plurality of rotor arms each include a rotor unit at a distal end of the rotor arm. The rotor units are configured to provide propulsion for the UAV. The plurality of hinge mechanisms mechanically attach (or couple) proximal ends of the plurality of rotor arms to the central body. Each hinge mechanism is configured to rotate a respective rotor arm of the plurality of rotor arms about an axis of rotation that is at an oblique angle relative to a vertical median plane of the central body to transition between an extended state and a folded state.

Abstract: The technology described herein relates to autonomous aerial vehicle technology and, more specifically, to image stabilization systems for autonomous aerial vehicles. In some embodiments, a UAV including a central body, an image capture assembly that couples the image capture assembly to the central body. The image stabilization assembly is configured to provide structural protection and support around the image capture assembly while passively isolating the image capture assembly from vibrations and other motion of the central body while the UAV is in flight.

Abstract: Methods and systems are described for new paradigms for user interaction with an unmanned aerial vehicle (referred to as a flying digital assistant or FDA) using a portable multifunction device (PMD) such as smart phone. In some embodiments, a user may control image capture from an FDA by adjusting the position and orientation of a PMD. In other embodiments, a user may input a touch gesture via a touch display of a PMD that corresponds with a flight path to be autonomously flown by the FDA.

Abstract: Embodiments are described for a stabilization system configured, in some embodiments, for stabilizing image capture from an aerial vehicle (e.g., a UAV). According to some embodiments, the stabilization systems employs both active and passive stabilization means. A passive stabilization assembly includes a counter-balanced suspension system that includes an elongated arm that extends into and is coupled to the body of a vehicle. The counter-balanced suspension system passively stabilizes a mounted device such as an image capture device to counter motion of the UAV while in use. In some embodiment the counter-balanced suspension system passively stabilizes a mounted image capture assembly that includes active stabilization means (e.g., a motorized gimbal and/or electronic image stabilization). In some embodiments, the active and passive stabilization means operate together to effectively stabilize a mounted image capture device to counter a wide range of motion characteristics.

Abstract: An actuator is introduced that utilizes the forces that result from placing a current carrying coil in a magnetic field to rotate a connected object about at least one axis. In some embodiments, the introduced coil actuator includes a coil of conductor coupled to an arm or other type of structural element that extends radially from an axis of rotation. The introduced coil actuator can be utilized to provide motion control in a variety of different applications such as gimbal mechanisms. In some embodiments, the introduced coil actuator can be implemented in a gimbal mechanism for adjusting an orientation of a device such as a camera relative to a connected platform such as the body of an aerial vehicle.

Abstract: Methods and systems are described for new paradigms for user interaction with an unmanned aerial vehicle (referred to as a flying digital assistant or FDA) using a portable multifunction device (PMD) such as smart phone. In some embodiments, a user may control image capture from an FDA by adjusting the position and orientation of a PMD. In other embodiments, a user may input a touch gesture via a touch display of a PMD that corresponds with a flight path to be autonomously flown by the FDA.

Abstract: An actuator is introduced that utilizes the forces that result from placing a current carrying coil in a magnetic field to rotate a connected object about at least one axis. In some embodiments, the introduced coil actuator includes a coil of conductor coupled to an arm or other type of structural element that extends radially from an axis of rotation. The introduced coil actuator can be utilized to provide motion control in a variety of different applications such as gimbal mechanisms. In some embodiments, the introduced coil actuator can be implemented in a gimbal mechanism for adjusting an orientation of a device such as a camera relative to a connected platform such as the body of an aerial vehicle.