Facebook Technologies, LLC

Microsoft Technology Licensing, LLC

Meta Platforms Technologies, LLC

Yi Zhao

Peter J Kaufman

Shayak Lahiri

Go Komatsu

Randall Richards Cook

Riccardo DeSalvo

Joseph Minh Tien

Andrea Cusano

Paolo Mattera

Roberto Parente

Giuseppe Castaldi

Vincenzo Galdi

Dustin Jeffery Gordon Krogstad

Pieter Willem Wigleven

Mark David Hogan

Embodiments described herein are directed to configuring managed computing devices utilizing containerized applications. For instance, a mobile device manager may provide configuration settings to a computing device via, for example, an enterprise network. A host operating system (OS) executing on the computing device determines and applies the settings that are applicable to the host OS. The configuration settings are stored for configuring containerized applications executing on the computing device. For instance, as new containerized applications are launched by the host OS, the containerized applications retrieve the configuration settings and determine and apply the settings that are applicable to the containerized applications. Results of applying the configuration settings to the host OS and the containerized applications are merged and sent to the mobile device manager. The host OS and the containerized application may, for example, implement the settings in order to be compliant with an enterprise's policy.

Configuration techniques for managed host operating systems and containerized applications instantiated thereby

Embodiments described herein are directed to configuring managed virtual machines. For instance, a management service (e.g., a mobile device manager) may provide configuration settings to a parent virtual machine. Upon successful application of the configuration settings, the parent virtual machine notifies a configuration service that it is in a steady state and provides the configuration settings to the configuration service. The configuration service notifies a cloud-based service (e.g., a virtual desktop service) that it is configured to instantiate virtual machines. The notification informs the cloud-based service that it is permitted to instantiate child virtual machines. Responsive to receiving the notification, the cloud-based service instantiates child virtual machine(s) as needed. To configure the child virtual machine(s), the configuration service provides the configuration settings received from the parent virtual machine to the child virtual machine(s), and the child virtual machine(s) configure themselves accordingly.

Configuration techniques for managed virtual machines

Magnetic sensor synchronization techniques for pose tracking in artificial reality systems include managing and sending, by one or more primary magnetic sensors, a wireless synchronization signal to other magnetic sensors to trigger sensing sampling. The primary magnetic sensor may generate and send sensor data to a wireless data hub that operates as a sensor data collector and transmits data for pose tracking in the system. Each of the other (non-primary) magnetic sensors, in response to receiving the wireless synchronization signal, updates its sampling starting clock based on new synchronization timing. Each of the magnetic sensors sends generated sensor data to its corresponding primary sensor or wireless data hub according to a different schedule to avoid conflicts between the various magnetic sensors. The synchronization process may be repeated a number of times if a sensor fails to receive or respond to a synchronization signal.

Synchronization of magnetic sensor sampling frequency for body pose tracking in artificial reality systems

A wearable magnetic sensor system includes a wearable article that spatially arranges magnetic sensor components around a user's torso to obtain magnetic sensor data used for body pose tracking. The wearable magnetic sensor system includes magnetic sensor components that sense a magnetic field generated by a magnetic transmitter. One or more wearable articles spatially arrange the magnetic sensor components at different locations on a body of the user, such as the arms and torso. The one or more wearable articles include a transmitter attachment mechanism for affixing the magnetic transmitter at, e.g., a torso of the user, and receiver attachment mechanisms for affixing the magnetic sensor components at, e.g., locations of the body other than the torso. The magnetic sensor components are spatially arranged at different locations on the user's body so as to maximize tracking accuracy and minimize interference between the magnetic sensors and the transmitter.

Artificial reality wearable magnetic sensor system for body pose tracking

A hand tracking system includes a wearable device configured to be worn on a user's wrist. The wearable device includes one or more transmitters, at least one receiver, and a controller. The transmitters generate an electric field that is altered by movement of a hand, fingers, and/or wrist of the user. The wearable device may also include one or more microphones that are configured to detect taps and so forth by one or more fingers of the hand. In some embodiments, the microphones are positioned such that they detect the taping my monitoring acoustic waves propagating through the tissue of the hand. The controller uses information captured by the receivers and/or the microphones and a model (e.g., machine learning model) to recognize a hand gesture.

Wearable gesture input device using electric impedance measurement

Multiple magnetic field generators have predetermined positions relative to a wearable device, such as a glove, and emit magnetic fields. Additionally, one or more magnetic field sensors are positioned on locations of the wearable device. A magnetic field sensor generates an output signal based on magnetic fields emitted by the magnetic field generator and detected by the magnetic field sensor. From the output signal and the predetermined positions of the magnetic field generators relative to the wearable device, a position and an orientation of the magnetic field sensor in a global coordinate system is determined. In some embodiments, a trained machine learning model is employed in conjunction with trilateration to obtain the position and orientation of the magnetic field sensor from its output signal.

Magnetic finger tracking with multi-frequency modulation

A system includes a locatable glove and a pose determination device. The locatable glove includes a glove body worn over a hand of a user, and a plurality of positioning transponders. The positioning transponders are coupled to the glove body at various positions on the glove body, and each re-radiates a received signal, the re-radiated signal unique to the positioning transponder. The pose determination device includes a plurality of antennas and a controller. The antennas are each configured to receive the unique signals re-radiated by the positioning transponders. The antennas are physically separated from each other. The controller is communicatively coupled to the plurality of antennas, and is configured to determine, for each of the received unique signals, a location of the position on the locatable glove of the positioning transponder corresponding to the unique signal.

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Redmond, WA, United States of America

Yi Zhao