Abstract: Embodiments relate to a suspension actuator system for a vehicle that includes an active control element, a passive control element and an adaptive damper which are mounted in series with one another along with a parallel spring.

Abstract: Generally described, one or more aspects of the present disclosure relate to the configuration and management of one or more components to facilitate dual axis rotation. More specifically, one or more aspects of the present application relate to the configuration or management of a rotation mechanism to facilitate the dual axis rotation of a display device. Illustratively, the display device is mounted on rotation mechanism that facilitates a dual axis rotation utilizing a single actuator, dual rotation joints, and associated linkages. The rotation component further includes at least one additional floating joint that provides additional tension forces relative to a third axis. Still further, in accordance with further embodiments, a control component can be utilized to generate control signals relating to rotation of the single actuators, such as establishing control positions and duty cycles.

Abstract: A method for manufacturing a dry electrode via a multi-roll calender system including providing the multi-roll calender system including a first, second, and third calendering rolls, each roll downstream from the next, where a first nip is formed between the first and second calendering rolls, and a second nip is formed between the second and third calendering rolls, rotating the first calendering roll at a first rotational velocity, rotating the second calendering roll at a second rotational velocity greater than the first rotational velocity, rotating the third calendering roll at a third rotational velocity greater than the second rotational velocity, delivering a first dry electrode material to the first nip to form a dry electrode film, delivering the dry electrode film to the second nip to form a tuned dry electrode film, and laminating the tuned dry electrode film to a current collector to form the dry electrode.

Abstract: A system may include a camera assembly, a fluid dispensing assembly, a wiper assembly, and a controller. The camera assembly can include a lens. The controller can be in communication with the camera assembly, the fluid dispensing assembly, and/or the wiper assembly. In some examples, the controller can be configured to determine, based on image quality data generated by the camera assembly, that a debris is attached to the lens. In response to determining that the debris is attached to the lens, the controller can trigger the fluid dispensing assembly to dispense liquid onto the lens, and activate the wiper assembly to remove the debris from the lens.

Abstract: Aspects of the present application correspond to utilization of a combined set of inputs from simulation systems to generate or train machine learned algorithms for utilization in vehicles with vision system-only based processing. Aspects of the present application correspond to utilization of a set of inputs from sensors or sensing systems and simulation systems to create updated training sets for use in machine learning algorithms. The combined set of inputs includes a first set of data corresponding to vision system from a plurality of cameras configured in a vehicle. The combined set of inputs further includes a second set of data corresponding to simulated content systems that generate additional training set data including visual images and data labels to supplement the vision system data.

Abstract: A system and methods for manufacturing a dry electrode for an energy storage device are disclosed. The system includes a first dry electrode material delivery system configured to deliver a dry electrode material, a first calendering roll, a second calendering roll, and a controller. The second calendering roll is configured to form a first nip between the first calendering roll and the second calendering roll. The first nip is configured to receive the dry electrode material from the first dry electrode material delivery system, and form a dry electrode film from the dry electrode material. The controller is configured to control a rotational velocity of the second calendering roll to be greater than a rotational velocity of the first calendering roll.

Abstract: Generally described, one or more aspects of the present disclosure relate to the configuration and management of one or more components to facilitate dual axis rotation. More specifically, one or more aspects of the present application relate to the configuration or management of a rotation mechanism to facilitate the dual axis rotation of a display device. Illustratively, the display device is mounted on rotation mechanism that facilitates a dual axis rotation utilizing a single actuator, dual rotation joints, and associated linkages. The rotation component further includes at least one additional floating joint that provides additional tension forces relative to a third axis. Still further, in accordance with further embodiments, a control component can be utilized to generate control signals relating to rotation of the single actuators, such as establishing control positions and duty cycles.

Abstract: Systems and methods for fail-safe corrective actions based on vision information for autonomous driving. An example method is implemented by a processor system included in a vehicle, with the method comprising obtaining images from image sensors positioned about the vehicle. Visibility information is determined for at least a portion of the images. Adjustment of operation of an autonomous vehicle is caused based on the visibility information.

Abstract: Systems and methods are described herein for a system to automatically execute actions associated with moveable closures of one or more trunk compartments of a vehicle. The system may detect a user device is within proximity of the vehicle using ultra-wideband signals. The system may then determine a location of the user device, and based on the location of the user device, whether the user device is within a trigger zone. A trigger zone may represent a real-world area positioned about a trunk compartment of the vehicle, the trunk compartment comprising a moveable closure. Based on determining that the user device is within a trigger zone, the system may execute an action associated with the moveable closure.

Abstract: Systems and methods are described herein for a system to automatically execute actions associated with one or more moveable closures of a vehicle. The system may detect a user device is within proximity of the vehicle using ultra-wideband signals. The system may then determine a location of the user device, and based on the location of the user device, whether the user device is within a trigger zone. A trigger zone may represent a real-world area positioned about the vehicle. Based on determining that the user device is within a trigger zone, the system may execute an action associated with the one or more moveable closures.

Abstract: Systems and methods for a vision-based machine learning model for autonomous driving with adjustable virtual camera. An example method includes obtaining images from a multitude of image sensors positioned about a vehicle. Features associated with the images are determined, with the features being output based on a forward pass through a first portion of a machine learning model. The features are projected into a vector space associated with a virtual camera at a particular height. The projected features are aggregated with other projected features associated with prior images. A plurality of objects which are positioned according to the virtual camera are determined.

Abstract: An annotation system uses annotations for a first set of sensor measurements from a first sensor to identify annotations for a second set of sensor measurements from a second sensor. The annotation system identifies reference annotations in the first set of sensor measurements that indicates a location of a characteristic object in the two-dimensional space. The annotation system determines a spatial region in the three-dimensional space of the second set of sensor measurements that corresponds to a portion of the scene represented in the annotation of the first set of sensor measurements. The annotation system determines annotations within the spatial region of the second set of sensor measurements that indicates a location of the characteristic object in the three-dimensional space.

Abstract: Presented herein are systems and methods for generating pathways for autonomously navigating through an environment. A computing system can identify a tensor comprising encodings derived from sensor data from an ego and map data defining a topology of an environment surrounding the ego. The computing system can determine, by applying at least a first portion of encodings to a machine learning (ML) model, a first index value defining a point within a first grid. The computing system can determine, by applying at least a second portion of encodings and the first index value to the ML model, a second index value defining the point within a second grid within the first grid. The computing system can generate a token for a pathway through the environment based on the first index value and the second index value for the point. The computing system can store a graph to include the token.

Abstract: Vehicular seat suspension systems that do not include scissor mechanisms or pivot joints to improve lateral stability and substantially eliminate deflection during operation, testing and/or crashes. In particular, the seat suspension systems include an inner element that is able to slide within a static outer element, allowing the system to bear high loads while ensuring lateral stability and substantially eliminating deflection experienced by convention seat suspension systems.

Abstract: Embodiments include systems and methods for processing sensor data and generating operational instructions of hardware of egos (e.g., autonomous vehicles, robots). The ego includes any number of machine-learning architectures, often neural network architectures, for processing sensor data and recognizing the environment around the ego and making decisions on the ego's behavior. The neural network architectures of the ego ingest sensor data and execute any number of operations related to a particular domain or task, such as object recognition or path planning, using the sensor data. A graph partitioner is trained to assign functions in the software of the neural networks and the sensor data to certain hardware processing units. Several compilers are used to generate the instructions based upon the assigned type of processing unit.

Abstract: A method comprises detecting one or more agent objects in a space around an ego object using image data captured by a camera of the ego object; storing a hierarchical nodal graph comprising a goal layer comprising one or more goal nodes and a plurality of interaction layers of interaction nodes subsequent to the goal layer; adding an interaction node to an interaction layer of interaction nodes of the plurality of interaction layers; determining a trajectory score for each of a plurality of trajectories based on one or more node scores of one or more nodes corresponding to the trajectory within the hierarchical nodal graph; and selecting a trajectory of the plurality of trajectories for the ego object based on the trajectory score for the trajectory.

Abstract: Disclosed herein are methods and systems for automatic labeling of image data for machine learning training purposes. A method comprises retrieving navigation data and image data from a set of egos navigating through an environment comprising at least one feature; generating a three-dimensional (3D) model of the environment using the navigation data and image data of at least a subset of the set of egos, the 3D model comprising a virtual representation of the at least one feature of the environment; identifying a machine learning label associated with the at least one feature within the image data; receiving second navigation data and second image data from a second ego not included within the set of egos, the second ego navigating the environment, the second image data including the at least one feature; automatically generating a machine learning label for the at least one feature depicted within the second image data.