Abstract: A head mounted display (HMD) includes a set of one or more lenses defining an optical axis, a display configured to project light through the set of the one or more lenses, a voice coil actuator coupled with the display and configured to move the display along the optical axis, and a first guide that is separate from the first voice coil actuator and coupled with the first display to guide the movement of the first display. The HMD additionally includes a set of one or more position sensors configured to determine a position of the display long the optical axis and an electronic controller configured to receive information identifying a reference position of the display along the optical axis and generate one or more electrical signals for initiating a movement of the first display toward the first reference point along the optical axis.

Abstract: A head-mounted display device includes one or more lenses and a display configured to provide visual data through the one or more lenses. The head-mounted display device also includes a direct-current (DC) motor mechanically coupled to the display, and the DC motor is configured to move the display along an axis by rotating a rotatable component of the DC motor. The head-mounted display device further includes: position sensor(s) configured to determine a position of the display, and electronic controller(s) in communication with the position sensor(s). The electronic controller(s) are configured to: (i) receive, from the position sensor(s), the determined position of the display as a first position of the display, (ii) receive information identifying a second position of the display, and (iii) generate electrical signal(s) that cause the DC motor to move the display from the first position to the second position along the axis.

Abstract: An agent interfaces with a sending computing device and a receiving computing device to automatically adjust one-way or two-way real-time audio and real-time video transmission parameters responsive to changing network conditions and/or application requirements. The agent incorporates a reinforcement learning model that adjusts transmission parameters to maximize an expected value of a sum of future rewards; the expected value of the sum of future rewards is based on a current state of the sending computing, a current action (e.g. a current set of transmission parameters) at the sending computing device and a reward provided by the receiving computing device. The reward is representative of a user-perceived quality of experience at the receiving computing device.

Abstract: An agent interfaces with a sending computing device and a receiving computing device to automatically adjust one-way or two-way real-time audio and real-time video transmission parameters responsive to changing network conditions and/or application requirements. The agent incorporates a reinforcement learning model that adjusts transmission parameters to maximize an expected value of a sum of future rewards; the expected value of the sum of future rewards is based on a current state of the sending computing, a current action (e.g. a current set of transmission parameters) at the sending computing device and a reward provided by the receiving computing device. The reward is representative of a user-perceived quality of experience at the receiving computing device.