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: 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 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: 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: A technique for user interaction with an autonomous unmanned aerial vehicle (UAV) is described. In an example embodiment, perception inputs from one or more sensor devices are processed to build a shared virtual environment that is representative of a physical environment. The sensor devices used to generate perception inputs can include image capture devices onboard an autonomous aerial vehicle that is in flight through the physical environment. The shared virtual environment can provide a continually updated representation of the physical environment which is accessible to multiple network-connected devices, including multiple UAVs and multiple mobile computing devices. The shared virtual environment can be used, for example, to display visual augmentations at network-connected user devices and guide autonomous navigation by the UAV.

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: Sports and fitness applications for an autonomous unmanned aerial vehicle (UAV) are described. In an example embodiment, a UAV can be configured to track a human subject using perception inputs from one or more onboard sensors. The perception inputs can be utilized to generate values for various performance metrics associated with the activity of the human subject. In some embodiments, the perception inputs can be utilized to autonomously maneuver the UAV to lead the human subject to satisfy a performance goal. The UAV can also be configured to autonomously capture images of a sporting event and/or make rule determinations while officiating a sporting event.

Abstract: An introduced autonomous aerial vehicle can include multiple cameras for capturing images of a surrounding physical environment that are utilized for motion planning by an autonomous navigation system. In some embodiments, the cameras can be integrated into one or more rotor assemblies that house powered rotors to free up space within the body of the aerial vehicle. In an example embodiment, an aerial vehicle includes multiple upward-facing cameras and multiple downward-facing cameras with overlapping fields of view to enable stereoscopic computer vision in a plurality of directions around the aerial vehicle. Similar camera arrangements can also be implemented in fixed-wing aerial vehicles.

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: A graphical user interface (GUI) for controlling the flight of an aircraft such as an unmanned aerial vehicle (UAV) is described. In example embodiments, the GUI includes a view of a physical environment from the perspective of the aircraft as well as various interactive elements through which a user can interact. The interactive elements presented in the GUI and the way in which user interaction with such elements is interpreted can depend on user selection from multiple available control modes. In some embodiments, user interaction with the GUI is interpreted based on a selected control mode and translated into behavioral objectives that are processed, along with other behavioral objectives, by a motion planner to maneuver the aircraft.

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: A technique is introduced for touchdown detection during autonomous landing by an aerial vehicle. In some embodiments, the introduced technique includes processing perception inputs with a dynamics model of the aerial vehicle to estimate the external forces and/or torques acting on the aerial vehicle. The estimated external forces and/or torques are continually monitored while the aerial vehicle is landing to determine when the aerial vehicle is sufficiently supported by a landing surface. In some embodiments, semantic information associated with objects in the environment is utilized to configure parameters associated with the touchdown detection process.