A light detection and ranging system can have an occlusion module connected to a light emitter and light detector with the light emitter and light detector each positioned behind a front glass. The occlusion module can be configured to generate an occlusion strategy in response to a real-time map of the front glass with the occlusion strategy populated with at least one operational alteration to correct for the presence of foreign matter indicated by the map of the front glass.

An optoelectronic module including a light emitter to generate light to be emitted from the module, a plurality of spatially distributed light sensitive elements arranged to detect light from the emitter that is reflected by an object outside the module, and one or more dedicated spurious-reflection detection pixels.

A contamination sensor for an optical sensor observation window includes a source, two prisms, a detector, and a controller. The source can emit a collimated light beam at an incident angle that is greater than a critical angle of an interface between a fluid and the window. The window has a refractive index greater than the refractive index of the fluid. The prisms can direct the collimated light beam within the window such that the collimated light beam reflects within a contamination detection zone of the window. The detector can receive the collimated light beam. The controller can communicate with the source and detector. The controller can calculate an emission/detection ratio defined by a difference between an amount of light emitted by the source and an amount of light that passes from the source to the detector by a total internal reflectance of the window.

A distance measuring apparatus includes an optical system abnormality detection section for detecting abnormalities of an optical system of the distance measuring apparatus by comparing a relationship between a measured distance value d and a light intensity Ls with a reference value K.sub.ρ, K.sub.ρ1, K.sub.Ls0d0, or K.sub.Ab0.

Aspects and implementations of the present disclosure address challenges of the existing technology by enabling lidar-assisted identification and characterization of visibility-reducing media (VRM) such as fog, rain, snow, dust in autonomous vehicle applications, using lidar sensing. VRM can be identified and characterized using a variety of techniques, including analyzing a spatial distribution of low-intensity lidar returns, detecting pulse elongation of VRM-returns associated with reflection from VRM, determining intensity of VRM-returns, determining reduction of intensity of returns from various reference objects, and other techniques.

In this obstacle detection system, if an obstacle has been detected by a front obstacle sensor or a rear obstacle sensor which has an obstacle detection range corresponding to the travel direction of the work vehicle, then a control unit displays the detected position of the obstacle on a display unit and performs collision avoidance control corresponding to the detection position of the obstacle; further, if an obstacle has been detected by a front obstacle sensor or a rear obstacle sensor which has an obstacle detection range not corresponding to the travel direction of the work vehicle, then the control unit displays the detected position of the obstacle on the display unit without performing collision avoidance control corresponding to the detection position of the obstacle.

Simulated degraded sensor data may be generated for use in training a model. For instance, first sensor data collected by a sensor of a perception system of an autonomous vehicle may be received and converted into the simulated degraded sensor data for a particular degrading condition, such as a weather-related degrading condition. Then, the simulated degraded sensor data may be used to train a model for evaluating performance of the perception system to detect objects external to the autonomous vehicle under one or more conditions.

An optoelectronic sensor, in particular a laser scanner, for detecting an object in a monitored zone is provided having a light transmitter for transmitting a light beam into the monitored zone; a light receiver for generating a received signal from the light beam remitted by the object; a moving deflection unit for a periodic deflection of the light beam to scan the monitored zone in the course of the movement; and having a control and evaluation unit that is configured to determine the time of flight between the transmission and reception of the light beam and to determine the distance from the object therefrom, wherein the sensor has a correction of the signal dynamics, i.e. of the relative reception power in dependence on the distance of the scanned object, The control and evaluation unit is here configured to correct the signal dynamics by adapting the sensitivity of the sensor.

A LIDAR system. The LIDAR system includes a light transmitting unit and a light receiving unit. A beam path is formed between the light transmitting unit and the light receiving unit of the LIDAR system, in order to optically scan surroundings of the LIDAR system during the operation of the LIDAR system. The LIDAR system is configured to recognize a contamination of the beam path, based on LIDAR measured data, which have been obtained during the optical scanning of the surroundings. A method for recognizing a contamination of a beam path of a LIDAR system is described, including recognizing the contamination by the LIDAR system based on LIDAR measured data, which have been obtained during an optical scanning of surroundings of the LIDAR system.

A method of tracking an object using a LiDAR sensor includes determining, by an information determiner, based on the spacing distance between a target point and a valid neighboring point disposed adjacent to the target point in the same layer as the target point, among first points acquired by the LiDAR sensor, noise information indicating whether the target point is a noise point; and clustering, by a clustering unit, the first points using the noise information.