Abstract: Systems and methods for learning and managing robot user interfaces are disclosed herein. One embodiment generates, based on input data including information about past interactions of a particular user with a robot and with existing HMIs of the robot, a latent space using one or more encoder neural networks, wherein the latent space is a reduced-dimensionality representation of learned behavior and characteristics of the particular user, and uses the latent space as input to train a decoder neural network associated with (1) a new HMI distinct from the existing HMIs or (2) a particular HMI among the existing HMIs to alter operation of the particular HMI. The trained first decoder neural network is deployed in the robot to control, at least in part, operation of the new HMI or the particular HMI in accordance with the learned behavior and characteristics of the particular user.

Abstract: A duration of time in which an individual observed a region can be determined. An image can be received. The image can include an indication of a point of gaze of the individual at a production time of the image. The image can include a visual fiducial marker, which can be disposed at a position in the image and can include a visual symbol. The visual symbol can be associated with data that define the region. The region can have a shape and a size and can be disposed a displacement in a direction from a position of the visual fiducial marker. Using the visual symbol, a location of an edge of the region can be determined. The indication of the point of gaze can be determined to be within the region. The production time of the image can be determined to be within the duration of time.

Abstract: Systems and methods for learning and managing robot user interfaces are disclosed herein. One embodiment generates, based on input data including information about past interactions of a particular user with a robot and with existing HMIs of the robot, a latent space using one or more encoder neural networks, wherein the latent space is a reduced-dimensionality representation of learned behavior and characteristics of the particular user, and uses the latent space as input to train a decoder neural network associated with (1) a new HMI distinct from the existing HMIs or (2) a particular HMI among the existing HMIs to alter operation of the particular HMI. The trained first decoder neural network is deployed in the robot to control, at least in part, operation of the new HMI or the particular HMI in accordance with the learned behavior and characteristics of the particular user.

Abstract: Systems and methods are provided for improved and intuitive adjustment of a vehicle headrest. A vehicle headrest adjustment system may include touch sensors and/or motion sensors to determine a driver or passenger intends to adjust a vehicle headrest. Upon detection of touch consistent with intent to adjust a vehicle headrest and/or a hand gesture consistent with intent to adjust a vehicle headrest, a system may unlock a vehicle headrest. A driver or passenger may move the unlocked vehicle headrest into the desired position. Upon detection of a condition indicating the driver or passenger is finished and/or upon a set period of time elapsing, the system may re-lock the vehicle headrest into place. A vehicle headrest adjustment system may also include a power-assist function. The power-assist function may include motors and force sensors to assist a driver or passenger in moving a vehicle headrest into a desired position.

Abstract: Systems and methods for controlling an autonomous vehicle are disclosed herein. One embodiment determines a reference path for the autonomous vehicle along a roadway segment and steers the autonomous vehicle along a path that includes controlled back and forth lateral deviations from the reference path along the roadway segment to provide feedback to an occupant of the autonomous vehicle, the feedback indicating to the occupant that the autonomous vehicle is in an autonomous driving mode and that the autonomous driving mode is operating correctly.

Abstract: A system is provided for implementing steering wheel controls, namely steering wheel rotation locking. In accordance with embodiments of the disclosed technology, a system may comprise a steering wheel rotation locking device; and a controller communicatively connected to the steering wheel rotation locking device to determine a presence and location of one or more objects or conditions surrounding a vehicle, and produce steering wheel control feedback to physically prevent rotational movement of a steering wheel.

Abstract: Systems and methods are provided for improved and intuitive adjustment of a vehicle headrest. A vehicle headrest adjustment system may include touch sensors and/or motion sensors to determine a driver or passenger intends to adjust a vehicle headrest. Upon detection of touch consistent with intent to adjust a vehicle headrest and/or a hand gesture consistent with intent to adjust a vehicle headrest, a system may unlock a vehicle headrest. A driver or passenger may move the unlocked vehicle headrest into the desired position. Upon detection of a condition indicating the driver or passenger is finished and/or upon a set period of time elapsing, the system may re-lock the vehicle headrest into place. A vehicle headrest adjustment system may also include a power-assist function. The power-assist function may include motors and force sensors to assist a driver or passenger in moving a vehicle headrest into a desired position.

Abstract: Systems and methods are provided for improved and intuitive adjustment of a vehicle headrest. A vehicle headrest adjustment system may include touch sensors and/or motion sensors to determine a driver or passenger intends to adjust a vehicle headrest. Upon detection of touch consistent with intent to adjust a vehicle headrest and/or a hand gesture consistent with intent to adjust a vehicle headrest, a system may unlock a vehicle headrest. A driver or passenger may move the unlocked vehicle headrest into the desired position. Upon detection of a condition indicating the driver or passenger is finished and/or upon a set period of time elapsing, the system may re-lock the vehicle headrest into place. A vehicle headrest adjustment system may also include a power-assist function. The power-assist function may include motors and force sensors to assist a driver or passenger in moving a vehicle headrest into a desired position.

Abstract: Systems and methods are provided for improved and intuitive adjustment of a vehicle headrest. A vehicle headrest adjustment system may include touch sensors and/or motion sensors to determine a driver or passenger intends to adjust a vehicle headrest. Upon detection of touch consistent with intent to adjust a vehicle headrest and/or a hand gesture consistent with intent to adjust a vehicle headrest, a system may unlock a vehicle headrest. A driver or passenger may move the unlocked vehicle headrest into the desired position. Upon detection of a condition indicating the driver or passenger is finished and/or upon a set period of time elapsing, the system may re-lock the vehicle headrest into place. A vehicle headrest adjustment system may also include a power-assist function. The power-assist function may include motors and force sensors to assist a driver or passenger in moving a vehicle headrest into a desired position.

Abstract: Systems and methods are provided for improved collision prevention. Systems and methods may provide for the prevention of rear-end vehicle collisions by locking the forward movement of the throttle pedal when a threshold is reached. An end stop or mechanical linkage may completely lock the throttle pedal in situations in which continued acceleration is likely to result in a rear-end collision. The systems and methods disclosed herein may provide from a complete locking of the throttle pedal which may physically avoid or eliminate a rear-end collision due to improper throttle actuation. The systems and methods disclosed herein may also improve a driver's mental model for safe driving by teaching a driver that certain maneuvers are not available in certain conditions.

Abstract: An easy entrance/exit system for a vehicle includes a vehicle seat, a pad, a pad-side magnetic device, and a seat-side magnet. The vehicle seat includes a seat base. The pad is supported atop the seat base for swiveling about a pivot point. The pad-side magnetic device is coupled to the pad at the pivot point. The seat-side magnet is within the seat base at the pivot point. The seat-side magnet is configured to apply a magnetic field to the pad-side magnetic device to govern swiveling of the pad about the pivot point.

Abstract: A duration of time in which an individual observed a region can be determined. An image can be received. The image can include an indication of a point of gaze of the individual at a production time of the image. The image can include a visual fiducial marker, which can be disposed at a position in the image and can include a visual symbol. The visual symbol can be associated with data that define the region. The region can have a shape and a size and can be disposed a displacement in a direction from a position of the visual fiducial marker. Using the visual symbol, a location of an edge of the region can be determined. The indication of the point of gaze can be determined to be within the region. The production time of the image can be determined to be within the duration of time.

Abstract: An easy entrance/exit system for a vehicle includes a vehicle seat, a pad, a pad-side magnetic device, and a seat-side magnet. The vehicle seat includes a seat base. The pad is supported atop the seat base for swiveling about a pivot point. The pad-side magnetic device is coupled to the pad at the pivot point. The seat-side magnet is within the seat base at the pivot point. The seat-side magnet is configured to apply a magnetic field to the pad-side magnetic device to govern swiveling of the pad about the pivot point.

Abstract: Systems and methods for controlling an autonomous vehicle are disclosed herein. One embodiment determines a reference path for the autonomous vehicle along a roadway segment and steers the autonomous vehicle along a path that includes controlled back and forth lateral deviations from the reference path along the roadway segment to provide feedback to an occupant of the autonomous vehicle, the feedback indicating to the occupant that the autonomous vehicle is in an autonomous driving mode and that the autonomous driving mode is operating correctly.

Abstract: System, methods, and other embodiments described herein relate to identifying when a situational awareness of a vehicle is inconsistent with a surrounding environment. In one embodiment, a method includes analyzing occupant sensor data about at least one occupant of the vehicle to generate a reaction level of the occupant. The reaction level characterizes at least a current response of the occupant to the surrounding environment and control of the vehicle within the surrounding environment. The method includes comparing an expected reaction for the occupant with the reaction level to determine whether the reaction level of the occupant correlates with the situational awareness of the vehicle about the surrounding environment. The method includes, in response to identifying that the reaction level does not correlate with the expected reaction, executing, by the vehicle, a responsive action to account for inconsistencies in the situational awareness of the vehicle.

Abstract: System, methods, and other embodiments described herein relate to identifying when a situational awareness of a vehicle is inconsistent with a surrounding environment. In one embodiment, a method includes analyzing occupant sensor data about at least one occupant of the vehicle to generate a reaction level of the occupant. The reaction level characterizes at least a current response of the occupant to the surrounding environment and control of the vehicle within the surrounding environment. The method includes comparing an expected reaction for the occupant with the reaction level to determine whether the reaction level of the occupant correlates with the situational awareness of the vehicle about the surrounding environment. The method includes, in response to identifying that the reaction level does not correlate with the expected reaction, executing, by the vehicle, a responsive action to account for inconsistencies in the situational awareness of the vehicle.