Surface penetrating radar interrogates a region adjacent a pathway of the vehicle in response to activation by a user. An object detection system which is responsive to the radar transceiver is configured to recognize one or more spatial signatures of one or more detected objects in the region. A controller coupled to the radar transceiver and the object detection system is configured to (i) compare a respective spatial signature of at least one of the detected objects to a plurality of predetermined target signatures to detect an infrastructure asset, (ii) assess a perimeter around the detected infrastructure asset to estimate a severity of an obstruction blocking the infrastructure asset, and (iii) convey an alert message to the user when the estimated severity is greater than a threshold.

An electronic device, a method, and computer readable medium are disclosed. The method includes transmitting radar signals via a radar transceiver. The method also includes identifying signals of interest that represent biometric information of a user based on reflections of the radar signals received by the radar transceiver. The method further includes generating an input based on the signals of interest that include the biometric information. The method additionally includes extracting a feature vector based on the input. The method also includes authenticating the user based on comparison of the feature vector to a threshold of similarity with preregistered user data.

Aspects of the disclosed technology provide solutions for performing odometry and in particular, for performing odometry by filtering moving objects from a scene using sensor data. In some aspects, a process can include steps for receiving a first set of sensor data corresponding with a plurality of objects in a scene, determining one or more moving objects and one or more stationary objects from among the plurality of objects, and receiving a second set of sensor data. In some aspects, the process can further include steps for filtering the second set of sensor data to remove data associated with the one or more moving objects and generating odometry data associated with the filtered second set of sensor data. Systems and machine-readable media are also provided.

A system for illuminating an area around a motor vehicle, having: a pair of radar systems and a pair of lighting systems mounted on the motor vehicle; a vehicle level sensor configured to detect changes in pitch or roll of the motor vehicle; and an illumination control system in the motor vehicle. The illumination control system includes a key fob communication system and determines the location of a person by detecting the person approaching the motor vehicle by detecting the presence of the key fob while also detecting the location of the person with a radar system mounted on the vehicle. Next, when the location of the person has been determined, the illumination system lights up the area the person is standing while following movement of the person with the radar system to continuously re-directing the illumination towards the location on the ground where the person is standing as the person moves.

Systems and methods are provided for utilizing sensor data from sensors of different modalities and from different vehicles to generate a combined image of an environment. Sensor data, such as a point cloud, generated by a LiDAR sensor on a first vehicle may be combined with sensor data, such as image data, generated by a camera on a second vehicle. The point cloud and image data may be combined to provide benefits over either data individually and processed to provide an improved image of the environment of the first and second vehicles. Either vehicle can perform this processing when receiving the sensor data from the other vehicle. An external system can also do the processing when receiving the sensor data from both vehicles. The improved image can then be used by one or both of the vehicles to improve, for example, automated travel through or obstacle identification in the environment.

Systems, methods, and devices for radio frequency (RF) ranging-aided localization and crowdsourced mapping are provided. In one aspect, a method performed by a user equipment (UE) includes obtaining sensor data comprising first radio frequency (RF) ranging data and imaging data. The method further includes tagging the first RF ranging data with location information and semantic information, wherein the semantic information is based on the imaging data, and wherein the semantic information indicates a first portion of the RF ranging data is associated with a static object type and a second portion of the RF ranging data is associated with a temporary-static object type different from the static object type. The method further includes transmitting, to a RF ranging assistance server, the first RF ranging data tagged with the location information and the semantic information.

Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for processing sensor data. In one aspect, a method includes obtaining image data representing a camera sensor measurement of a scene; obtaining radar data representing a radar sensor measurement of the scene; generating a feature representation of the image data; generating a respective initial depth estimate for each of a subset of the plurality of pixels; generating a feature representation of the radar data; for each of the subset of the plurality of pixels, generating a respective adjusted depth estimate for the pixel using the initial depth estimate for the pixel and the radar feature vectors for a corresponding subset of the plurality of radar reflection points; generating a fused point cloud that includes a plurality of three-dimensional data points; and processing the fused point cloud to generate an output that characterizes the scene.

Disclosed are systems, apparatuses, processes, and computer-readable media to implement a heterogenous biometric authentication process in a control system. A process includes obtaining radar information identifying measured properties of at least one object in an environment, generating pre-processed radar information for input into a neural network at least in part by processing the obtained radar information, generating an object detection output for the at least one object at least in part by detecting the at least one object using the neural network with the pre-processed radar information as input, and modifying, based on the obtained radar information, the object detection output for the at least one object.

In one embodiment, a modular sensor assembly configured for mounting on a vehicle includes a first set of sensors and a second set of sensors. The modular sensor assembly includes a coordinate frame baseplate including a continuous surface, and sensor mounting elements coupled to the continuous surface for mounting the first set of sensors at a first height. The coordinate frame baseplate includes a sensor platform configured for mounting the second set of sensors at a second height. The first set of sensors and the second set of sensors are coupled to the coordinate frame baseplate so as to impart a common coordinate frame for the first set of sensors mounted at the first height and the second set of sensors mounted at the second height. The modular sensor assembly includes a bridging support structure coupled to the coordinate frame baseplate and capable of being mounted on a vehicle.

A method includes generating a first warped image based on a pose and a depth estimated from a current image and a previous image in a sequence of images captured by a camera of the agent. The method also includes estimating a motion of dynamic object between the previous image and the target image. The method further includes generating a second warped image from the first warped image based on the estimated motion. The method still further includes controlling an action of an agent based on the second warped image.