A sensing system. In some embodiments, the system includes a first imaging radio frequency receiver, a second imaging radio frequency receiver, a first optical beam combiner, a first imaging optical receiver, a second optical beam combiner, and an optical detector array. The first optical beam combiner may be configured to combine optical signals of the imaging radio frequency receivers. The second optical beam combiner may be configured to combine the optical signals of the imaging radio frequency receivers, and the optical signal of the first imaging optical receiver.

A target object detection apparatus (20) includes an image generation unit (220) that generates, from three-dimensional information acquired by processing a reflection wave of an electromagnetic wave irradiated toward an inspection target, a two-dimensional image of the inspection target viewed from a predetermined direction; an area detection unit (230) that detects, from the two-dimensional image, each of at least two detection areas of detection target objects recognized by using at least two recognition means; and an identification unit (240) that identifies the detection target object, based on a positional relationship between the detected at least two detection areas.

An apparatus and the like for controlling a mobile body that are capable of adjusting a detection result by a radar device in accordance with a three-dimensional shape for each region of a three-dimensional map generated from an image captured by an image-capturing device are provided. A mobile body control unit 105 is an apparatus for controlling the vehicle (mobile body) including an image-capturing device 101 and a millimeter wave radar device 102 (radar device). A three-dimensional map generation unit 203 generates a three-dimensional map around the vehicle from an image captured by the image-capturing device 101. A radar weight map estimation unit 204 (weight estimation unit) estimates the weight of the detection result by the millimeter wave radar device 102 for each region of the three-dimensional map from the three-dimensional shape for each region of the three-dimensional map. A weight adjustment unit 205 (adjustment unit) adjusts a detection result by the millimeter wave radar device 102 on the basis of a weight.

A plurality of images can be acquired from a plurality of sensors and a plurality of flattened patches can be extracted from the plurality of images. An image location in the plurality of images and a sensor type token identifying a type of sensor used to acquire an image in the plurality of images from which the respective flattened patch was acquired can be added to each of the plurality of flattened patches. The flattened patches can be concatenated into a flat tensor and add a task token indicating a processing task to the flat tensor, wherein the flat tensor is a one-dimensional array that includes two or more types of data. The flat tensor can be input to a first deep neural network that includes a plurality of encoder layers and a plurality of decoder layers and outputs transformer output. The transformer output can be input to a second deep neural network that determines an object prediction indicated by the token and the object predictions can be output.

A plurality of images can be acquired from a plurality of sensors and a plurality of flattened patches can be extracted from the plurality of images. An image location in the plurality of images and a sensor type token identifying a type of sensor used to acquire an image in the plurality of images from which the respective flattened patch was acquired can be added to each of the plurality of flattened patches. The flattened patches can be concatenated into a flat tensor and add a task token indicating a processing task to the flat tensor, wherein the flat tensor is a one-dimensional array that includes two or more types of data. The flat tensor can be input to a first deep neural network that includes a plurality of encoder layers and a plurality of decoder layers and outputs transformer output. The transformer output can be input to a second deep neural network that determines an object prediction indicated by the token and the object predictions can be output.

Systems and methods for route synchronization between two or more robots to allow for a single training run of a route to effectively train multiple robots to follow the route.

The disclosed technology provides solutions for validating operation of a sensor assembly by performing an assembly test. In some aspects, a process of performing the assembly test includes steps for collecting motor controller measurements, wherein the motor controller measurements include an amount of current supplied to a motor coupled when performing a sensor sweep, calculating an average current drawn by the motor based on the current measurements, and calculating a peak current drawn by the motor based on the current measurements. In some aspects, the process can further include steps for determining if the sensor assembly passes the sensor assembly test based on the average current drawn and the peak current drawn. Systems and machine-readable media are also provided.

A method for forming 3D image data representative of the subsurface of infrastructure located in the vicinity of a moving vehicle. The method includes: rotating a directional antenna, mounted to the moving vehicle, about an antenna rotation axis; performing, using the directional antenna whilst it is rotated about the antenna rotation axis, a plurality of collection cycles in which the directional antenna emits RF energy and receives reflected RF energy; collecting, during each of the plurality of collection cycles performed by the directional antenna.

A method for forming 3D image data representative of the subsurface of infrastructure located in the vicinity of a moving vehicle. The method includes: rotating a directional antenna, mounted to the moving vehicle, about an antenna rotation axis; performing, using the directional antenna whilst it is rotated about the antenna rotation axis, a plurality of collection cycles in which the directional antenna emits RF energy and receives reflected RF energy; collecting, during each of the plurality of collection cycles performed by the directional antenna.

Provided are systems and methods of using of optical delay lines in RF imagers, e.g., Ultra-wideband (UWB) imagers. In an embodiment, a modulator can be configured to convert radio-frequency signals to optical signal. First and second optical delay lines delay respective first and second optical signals converted by the modulator, and a photodetector can convert the delayed optical signals to at least one electrical signal corresponding to at least one pixel of a radio frequency image. The disclosed systems and methods can also further form a radio-frequency image based on output from the photodetector. In still further embodiments, the photodetector can receive modulated optical signals from an array of optical delays. Also provided are related methods of using the disclosed systems and devices.