Abstract: In various examples, optical flow-based algorithms may be used to detect objects in an environment by computing displacement fields for images captured using asynchronous cameras. As an example, an asynchronous set of cameras (e.g., two or more cameras) may capture a series of asynchronous images of an environment. Additionally, in some examples, the cameras may be positioned at different locations and capture different fields of view of the environment. Based at least on the differing image capture times and/or the differing fields of view of the images, image pixels corresponding to the same, physical locations in the environment may move locations between images of the series of images. The disclosed systems and methods may use optical flow algorithms to compute scores associated with the displacement/movement of the pixels throughout the series of images, as well as use these scores to detect objects in the environment.

Abstract: Embodiments of the present disclosure relate to correction of LiDAR measurement bias. In some embodiments, a LiDAR measurement bias such as a range-dependent height offset and/or a reflectivity-dependent height offset may be estimated in an offline process, the estimated biases may be stored in any suitable way (e.g., in one or more look up tables, indexed by range and/or reflectivity), and LiDAR points measured during an online process may be compensated by looking up and subtracting a range-dependent height bias corresponding to the measured range, and/or by looking up and subtracting a reflectivity-dependent height bias corresponding to the measured reflectivity.

Abstract: Embodiments of the present disclosure relate to ground surface estimation using localized surface fitting. A three-dimensional (3D) surface structure (e.g., a road surface profile) may be estimated using a nonlinear optimization to fit height values to (e.g., accumulated, bias-corrected) LiDAR detections (e.g., sampled in localized regions along one or more predicted trajectories). For example, LiDAR data (e.g., detected 3D point clouds) may be ego-motion compensated, corrected for measurement bias, accumulated, and sampled along one or more predicted trajectories, and the height of each trajectory point may be fitted to the heights of the corresponding sampled points using a nonlinear optimization. As such, the resulting road surface profile (e.g., modeled along the wheel track(s)) may be provided to an adaptive suspension control system to modulate the damping characteristic of the suspension system to counteract indentations (e.g., potholes) or protrusions (e.g.

Abstract: Embodiments of the present disclosure relate to surface estimation using stereo imaging and surface disparities. For example, a three-dimensional (3D) surface structure may be modeled as a disparity field, and a surface disparity field representing a surface in the environment (e.g., the ground) may be generated using a constrained nonlinear hierarchical optimization to process stereo image data and iteratively refine estimated surface disparity values based on weights that guide the optimization to expected surface values (e.g., ground, road). The resulting surface (e.g., ground) disparity field may be used for a variety of downstream tasks, such as obstacle detection, segmentation of a navigable space, ego-motion refinement, and/or generation of an estimated surface profile.

Abstract: Embodiments of the present disclosure relate to surface estimation using stereo imaging and surface disparities. For example, a surface disparity field representing a surface in the environment (e.g., the ground) may be estimated from stereo image data and used for various downstream tasks. For example, the difference between a stereo disparity field and a ground disparity field may be used to detect objects, a representation of a navigable space may be generated by radially casting 2D rays in the ground disparity field, the ground disparity field may be used to compensate ego-motion for high dynamic attitude changes, and/or the ground disparity field may be lifted to 3D and used to fit a surface profile to points sampled from the lifted point cloud.

Abstract: Embodiments relate to hazard detection in autonomous and semi-autonomous systems and applications. A transformer may use sampled image and LiDAR features to extract and decode a representation of whether there is a hazard at the 3D location corresponding to each initial transformer query, the shape of the hazard, and/or its class. These detections may be provided to one or more control components of an autonomous vehicle, which may use the detections to navigate, plan, or otherwise perform one or more operations (e.g., obstacle avoidance, lane keeping, lane changing, merging, splitting, etc.). Some embodiments employ an automated approach to derive ground truth data from sensor data collected by data collection vehicle(s), such as data representing detected static scene points, navigable space boundaries, or detected hazard objects. Accordingly, hazards such as road debris and other obstacles may be detected and ground truth data may be generated for a variety of sensing tasks.

Abstract: Embodiments relate to hazard detection in autonomous and semi-autonomous systems and applications. A transformer may use sampled image and LiDAR features to extract and decode a representation of one or more features of each point (e.g., refined height, range, driving condition, etc.) on a sampled surface (e.g., the road). These detections may be provided to one or more control components of an autonomous vehicle, which may use the detections to navigate, plan, or otherwise perform one or more operations. Some embodiments employ an automated approach to derive ground truth data from sensor data collected by data collection vehicle(s), such as data representing detected ground surface models, detected surface features, detected weather and/or surface condition labels, and/or detected per-point artifact labels. Accordingly, surface features such as ground surface heights along a predicted trajectory may be detected and ground truth data may be generated for a variety of sensing tasks.

Abstract: In various examples, a surface may be estimated using depth data for autonomous systems and applications. One or more software components or modules may use the depth data (e.g., 3D LiDAR point cloud data) in addition to ego-motion data (e.g., data representative of location, heading, speed, and/or pose of the ego-machine) to generate a non-parametric model of the ground or driving surface. In some embodiments, an iterative process may be used to generate and iteratively refine estimated surface values by minimizing (or approximating minimization of) a cost function that penalizes deviation between measured values and estimated values and/or deviations among adjacent measured values. The systems and applications described herein may include robust real-time or near real-time ground surface estimation relying on generated data, and may further include a large-scale offline ground surface estimation approach that is non-causal and uses (e.g., all) available data at once.

Abstract: Aerial vehicles that are equipped with one or more imaging devices may detect obstacles that are small in size, or obstacles that feature colors or textures that are consistent with colors or textures of a landing area, using pairs of images captured by the imaging devices. Disparities between pixels corresponding to points of the landing area that appear within each of a pair of the images may be determined and used to generate a reconstruction of the landing area and a difference image. If either the reconstruction or the difference image indicates the presence of one or more obstacles, a landing operation at the landing area may be aborted or an alternate landing area for the aerial vehicle may be identified accordingly.

Abstract: Aerial vehicles that are equipped with one or more imaging devices may detect obstacles that are small in size, or obstacles that feature colors or textures that are consistent with colors or textures of a landing area, using pairs of images captured by the imaging devices. Disparities between pixels corresponding to points of the landing area that appear within each of a pair of the images may be determined and used to generate a reconstruction of the landing area and a difference image. If either the reconstruction or the difference image indicates the presence of one or more obstacles, a landing operation at the landing area may be aborted or an alternate landing area for the aerial vehicle may be identified accordingly.

Abstract: Aerial vehicles that are equipped with one or more imaging devices may detect obstacles that are small in size, or obstacles that feature colors or textures that are consistent with colors or textures of a landing area, using pairs of images captured by the imaging devices. Disparities between pixels corresponding to points of the landing area that appear within each of a pair of the images may be determined and used to generate a reconstruction of the landing area and a difference image. If either the reconstruction or the difference image indicates the presence of one or more obstacles, a landing operation at the landing area may be aborted or an alternate landing area for the aerial vehicle may be identified accordingly.

Abstract: Aerial vehicles that are equipped with one or more imaging devices may detect obstacles that are small in size, or obstacles that feature colors or textures that are consistent with colors or textures of a landing area, using pairs of images captured by the imaging devices. Disparities between pixels corresponding to points of the landing area that appear within each of a pair of the images may be determined and used to generate a reconstruction of the landing area and a difference image. If either the reconstruction or the difference image indicates the presence of one or more obstacles, a landing operation at the landing area may be aborted or an alternate landing area for the aerial vehicle may be identified accordingly.

Abstract: Many imaging scenarios involve an achromatic image (e.g., a panchromatic image or a near-infrared image) and one or more concurrently captured monochromatic images (e.g., RGB images captured through a Bayer filter array), and the compositing of these images through de-mosaicing and/or pan-sharpening to generate a high-resolution color image. However, in many such scenarios, the monochromatic images may exhibit distortion of edge geometry, resulting in artifacts and/or color distortions near visual edges of the composite image. However, such distortions may be absent from the achromatic image, and edge geometry may be represented as an intensity gradient among respective neighborhoods of achromatic pixels. Presented herein are techniques for reducing such distortions in monochromatic images through iterative adjustment of monochromatic pixel intensity to reflect the gradients of the neighborhoods of the corresponding achromatic pixels.

Abstract: A motor vehicle drive train device has a multi-group transmission that includes a main group, a front-mounted group upstream from the main group, and/or a downstream group downstream from the main group, and a control/regulation unit. The motor vehicle drive train device is provided for shifting, at least in one transmission gear change operation, the front-mounted group and/or the downstream group into neutral before engaging a target gear in the main group. The control/regulation unit is provided for shifting the front-mounted group and/or the downstream group into neutral in the transmission gear change operation only after at least partial synchronization of the main group.

Abstract: A motor vehicle drive train device has a multi-group transmission that includes a main group, a front-mounted group upstream from the main group, and/or a downstream group downstream from the main group, and a control/regulation unit. The motor vehicle drive train device is provided for shifting, at least in one transmission gear change operation, the front-mounted group and/or the downstream group into neutral before engaging a target gear in the main group. The control/regulation unit is provided for shifting the front-mounted group and/or the downstream group into neutral in the transmission gear change operation only after at least partial synchronization of the main group.

Abstract: Many imaging scenarios involve an achromatic image (e.g., a panchromatic image or a near-infrared image) and one or more concurrently captured monochromatic images (e.g., RGB images captured through a Bayer filter array), and the compositing of these images through de-mosaicing and/or pan-sharpening to generate a high-resolution color image. However, in many such scenarios, the monochromatic images may exhibit distortion of edge geometry, resulting in artifacts and/or color distortions near visual edges of the composite image. However, such distortions may be absent from the achromatic image, and edge geometry may be represented as an intensity gradient among respective neighborhoods of achromatic pixels. Presented herein are techniques for reducing such distortions in monochromatic images through iterative adjustment of monochromatic pixel intensity to reflect the gradients of the neighborhoods of the corresponding achromatic pixels.

Abstract: In a motor vehicle drive arrangement having an electric motor with a rotor for driving an oil pump and being supported in an air space of a housing by a rotor disk of the rotor of the electric motor which is permanently connected to a pump rotor of the oil pump, a freewheeling mechanism for a mechanical drive of the pump rotor of the oil pump is provided for coupling the oil pump to a vehicle travel drive train of the vehicle drive arrangement when the travel drive train rotates faster than the electric motor.

Abstract: In a motor vehicle drive arrangement oil is supplied to a drive gear mechanism and other drive elements by an oil pump which is driven only by an electric motor and is arranged in a space in which one or more torque transmission devices such as a hydrodynamic torque converter, an operable drive clutch and at least one electric motor for forming a hybrid drive are disposed and which is formed between the oil pump and electric motor, on the one hand, and the vehicle travel drive motor on the other, the oil pump is disposed around a shaft transmitting the drive torque to the transmission and is surrounded by the electric motor driving the pump.

Abstract: In a motor vehicle drive arrangement oil is supplied to a drive gear mechanism and other drive elements by an oil pump which is driven only by an electric motor and is arranged in a space in which one or more torque transmission devices such as a hydrodynamic torque converter, an operable drive clutch and at least one electric motor for forming a hybrid drive are disposed and which is formed between the oil pump and electric motor, on the one hand, and the vehicle travel drive motor on the other, the oil pump is disposed around a shaft transmitting the drive torque to the transmission and is surrounded by the electric motor driving the pump.