Abstract: A mobile device determines a vision based pose using images captured by a camera and determines a sensor based pose using data from inertial sensors, such as accelerometers and gyroscopes. The vision based pose and sensor based pose are used separately in a visualization application, which displays separate graphics for the different poses. For example, the visualization application may be used to calibrate the inertial sensors, where the visualization application displays a graphic based on the vision based pose and a graphic based on the sensor based pose and prompts a user to move the mobile device in a specific direction with the displayed graphics to accelerate convergence of the calibration of the inertial sensors. Alternatively, the visualization application may be a motion based game or a photography application that displays separate graphics using the vision based pose and the sensor based pose.

Abstract: Systems, apparatus and methods for estimating gravity and/or scale in a mobile device are presented. A difference between an image-based pose and an inertia-based pose is using to update the estimations of gravity and/or scale. The image-based pose is computed from two poses and is scaled with the estimation of scale prior to the difference. The inertia-based pose is computed from accelerometer measurements, which are adjusted by the estimation for gravity.

Abstract: An accelerometer in a mobile device is calibrated by taking multiple measurements of acceleration vectors when the mobile device is held stationary at different orientations with respect to a plane normal. A circle is calculated that fits respective tips of measured acceleration vectors in the accelerometer coordinate system. The radius of the circle and the lengths of the measured acceleration vectors are used to calculate a rotation angle for aligning the accelerometer coordinate system with the mobile device surface. A gyroscope in the mobile device is calibrated by taking multiple measurements of a rotation axis when the mobile device is rotated at different rates with respect to the rotation axis. A line is calculated that fits the measurements. The angle between the line and an axis of the gyroscope coordinate system is used to align the gyroscope coordinate system with the mobile device surface.

Abstract: An accelerometer located within a mobile device is used to estimate a gravity vector on a target plane in a world coordinate system. The accelerometer makes multiple measurements, each measurement being taken when the mobile device is held stationary on the target plane and a surface of the mobile device faces and is in contact with a planar portion of the target plane. An average of the measurements is calculated. A rotational transformation between an accelerometer coordinate system and a mobile device's coordinate system is retrieved from a memory in the mobile device, where the mobile device's coordinate system is aligned with the surface of the mobile device. The rotational transformation is applied to the averaged measurements to obtain an estimated gravity vector in a world coordinate system defined by the target plane.

Abstract: An apparatus and method for generating parameters for an application, such as an augmented reality application (AR app), using camera pose and gyroscope rotation is disclosed. The parameters are estimated based on pose from images and rotation from a gyroscope (e.g., using least-squares estimation with QR factorization or a Kalman filter). The parameters indicate rotation, scale and/or non-orthogonality parameters and optionally gyroscope bias errors. In addition, the scale and non-orthogonality parameters may be used for conditioning raw gyroscope measurements to compensate for scale and non-orthogonality.

Abstract: Vision based tracking of a mobile device is used to remotely control a robot. For example, images captured by a mobile device, e.g., in a video stream, are used for vision based tracking of the pose of the mobile device with respect to the imaged environment. Changes in the pose of the mobile device, i.e., the trajectory of the mobile device, are determined and converted to a desired motion of a robot that is remote from the mobile device. The robot is then controlled to move with the desired motion. The trajectory of the mobile device is converted to the desired motion of the robot using a transformation generated by inverting a hand-eye calibration transformation.

Abstract: A multi-dimensional sensor, a magnetometer or accelerometer, is calibrated based on the raw data provided by the sensor. Raw data is collected and may be used to generate ellipse or ellipsoid parameters, for a two-dimensional or three-dimensional sensor, respectively. An offset calibration factor is calculated based on the raw data, e.g., the determined ellipse or ellipsoid parameters. A sensitivity calibration factor is then calculated based on the offset calibration factor and the raw data. A non-orthogonality calibration factor can then be calculated based on the calculated offset and sensitivity calibration factors. Using the offset, sensitivity and non-orthogonality calibration factors, the raw data can be corrected to produce calibrated data.

Abstract: A displacement device for mapping wireless signal fingerprints includes motion sensors and at least one of a received signal strength indicator (RSSI) sensor and a round trip time (RTT) sensor. The motion sensors may include a pedometer and one or more sensors to receive turn information. The start position of the displacement device is initialized and as the displacement device is moved through an environment, the position of each measurement location is determined using the initialized position and data from the motion sensors. The measurement position along with the RSSI and/or RTT measurement is stored in a database, from which a map can be generated. The position of the access point may be determined using the RSSI measurement or RTT measurement. Additionally, accumulated errors in the measurement position may be monitored and when greater than a threshold, a user may be prompted to reinitialize the position of the displacement device.

Abstract: A mobile device compensates for a lack of a time stamp when an image frame is captured by estimating the frame time stamp latency. The mobile device captures images frames and time stamps each frame after the frame time stamp latency. A vision based rotation is determined from a pair of frames. A plurality of inertia based rotations is measured using time stamped signals from an inertial sensor in the mobile device based on different possible delays between time stamping each frame and time stamps on the signals from the inertial sensors. The determined rotations may be about the camera's optical axis. The vision based rotation is compared to the plurality of inertia based rotations to determine an estimated frame time stamp latency, which is used to correct the frame time stamp latency when time stamping subsequently captured frames. A median latency determined using different frame pairs may be used.

Abstract: A mobile device tracks a relative pose between a camera and a target using Vision aided Inertial Navigation System (VINS), that includes a contribution from inertial sensor measurements and a contribution from vision based measurements. When the mobile device detects movement of the target, the contribution from the inertial sensor measurements to track the relative pose between the camera and the target is reduced or eliminated. Movement of the target may be detected by comparing vision only measurements from captured images and inertia based measurements to determine if a discrepancy exists indicating that the target has moved. Additionally or alternatively, movement of the target may be detected using projections of feature vectors extracted from captured images.

Abstract: Apparatus for and method of processing sensor data for the purpose of navigating a vehicle (for example an autonomous or semi-autonomous vehicle), the sensor data being from a sensor (for example a camera) mounted on the vehicle. The method can include can include: for a number of time-steps, measuring a value of a parameter of a scene using the sensor to produce a sequence of images of the scene; determining a value of one or more image quality metrics (for example, spatial entropy and spatial information) in each image in the sequence; and identifying as either valid or invalid, a sub-sequence of images in the sequence based on the determined metric values.

Abstract: Methods and apparatuses are provided that may be implemented in a wireless signaling environment to provide certain location services. The location services may, for example, be based at least in part on positioning information associated with positioned wireless signaling measurements associated with wireless terminals. The location services may comprise location using signal pattern matching, location using observed timing differences, location using fine time assistance, location of significant network events and location distribution of terminals over a certain coverage area.

Abstract: An apparatus and method for a framework exposing an API (application programming interface) to web-based server applications on the internet or in the cloud is presented. The API allows server applications to retrieve sensor data from a mobile device via a low-power sensor core processor on a mobile device. This API eliminates effort and cost associated with developing and promoting a new mobile device client application. The API framework includes APIs that web-based application may use to fetch sensor data from one or more particular sensors on the mobile device.

Abstract: The method and apparatus as described are directed toward techniques and mechanisms to improve access terminal battery life through search rate control. Controlling the rate at which access terminals search for alternate networks in a cell, and more particularly reducing unnecessary attempts, significantly increases the battery life of the access terminal.

Abstract: A homography between two captured images of a planar object is decomposed into at least one possible solution, and typically at least two ambiguous solutions. The ambiguity between the two solutions is removed, or a single solution validated, using measurements from orientation sensors. The measurements from orientation sensors may be used by comparing at least one of the yaw, pitch, and/or roll angles derived from a relative rotation matrix for the one or more solutions to a corresponding at least one of the yaw, pitch, and/or roll angles derived from the measurements from the orientation sensors.

Abstract: Methods and apparatuses are provided that may be implemented in a mobile device to establish an orientation invariant reference frame based, at least in part, on measurement values from a three-dimensional accelerometer fixed to the mobile device; transform subsequent inertial sensor measurements to the reference frame; and classify a motion state of the mobile device relative to the reference frame based, at least in part, on the transformed inertial sensor measurements.

Abstract: Example methods, apparatuses, or articles of manufacture are disclosed herein that may be utilized, in whole or in part, to facilitate or support one or more operations or techniques for reducing power consumption or error of a digital compass.

Abstract: Systems and methods are described for measuring orientation of sensors associated with a mobile device with respect to pedestrian motion of a user of the mobile device. An example technique described herein includes obtaining acceleration information associated with the mobile device, partitioning the acceleration information according to respective detected pedestrian steps of the user, identifying a forward motion direction of the user of the mobile device based on the acceleration information and the detected pedestrian steps, and computing a misalignment angle between the forward motion direction of the user of the mobile device and an orientation of the mobile device.

Abstract: Techniques for using measurements made by UEs to improve network performance are described. In one aspect, RF parameters of cells may be determined by taking into account mobility of the UEs. Mobility information for the UEs may be determined based on measurement report messages (MRMs) sent by these UEs for handover. RF parameters such as antenna down-tilt, antenna orientation, antenna pattern, and/or pilot power of the cells may be determined based on the mobility information for the UEs. In another aspect, the RF parameters of cells may be dynamically adjusted based on loading conditions of cells. In yet another aspect, the location of a UE may be determined based on an MRM sent by the UE for handover. The MRM may include timing measurements for multiple cells. The location of the UE may be determined based on the timing measurements.

Abstract: A centrifugal pump has a stationary diffuser with a bore. A thrust bearing has a tubular portion that inserts into the bore. The thrust bearing has an external shoulder that contacts a support surface in the bore of the diffuser for transmitting downward thrust from an upstream impeller to the diffuser. The thrust bearing has an internal shoulder for transmitting upward thrust from a downstream impeller to the diffuser.