There is provided a distance measurement device that can appropriately detect a distance to an object regardless of the distance. The distance measurement device includes a laser light source, a photodetector, and a controller. The controller performs a long-distance routine that detects timing for receiving light when an object is at a long distance, and a short-distance routine that detects the timing for receiving light when the object is at a short distance, based on a detection signal output from the photodetector during one distance measurement operation. The controller then selects one of a detection result of the timing for receiving light by the long-distance routine and a detection result of the timing for receiving light by the short-distance routine, and calculates the distance to the object irradiated with projection light based on the selected detection result.

A parameter adjustment device (500) adjusts a parameter relating to control of laser light emitted from a measurement sensor (210) onto an object. A parameter calculator (520) calculates the parameter by applying, to a trained model generated through machine learning using training data sets each including waveform data of an amount of light received by the measurement sensor (210) and data indicating the parameter used to acquire the waveform data, waveform data newly acquired in a new state. The parameter calculated by the parameter calculator (520) enables measurement of the object using the measurement sensor (210) in the new state. A parameter outputter (530) outputs data indicating the parameter calculated by the parameter calculator (520).

Disclosed herein is method and system for determining correctness of Lidar sensor data used for localizing autonomous vehicle. The system identifies one or more Region of Interests (ROIs) in Field of View (FOV) of Lidar sensors of autonomous vehicle along a navigation path. Each ROI includes one or more objects. Further, for each ROI, system obtains Lidar sensor data comprising one or more reflection points corresponding to the one or more objects. The system forms one or more clusters in each ROI. The system identifies a distance value between, one or more clusters projected on 2D map of environment and corresponding navigation map obstacle points, for each ROI. The system compares distance value between one or more clusters and obstacle points based on which correctness of Lidar sensor data is determined. In this manner, present disclosure provides a mechanism to detect correctness of Lidar sensor data for navigation in real-time.

A laser perception-based method for spatial positioning of an agricultural robot: erecting a laser radar with a ranging function in a positioning space, setting a three-dimensional coordinate system, and conducting scanning using the laser radar to obtain point cloud data of an object in the positioning space, where the point cloud data include an azimuth and a distance with respect to the laser radar; installing a laser receiver on the agricultural robot, receiving a laser radar signal using the laser receiver during movement, when a laser beam emitted by the laser radar irradiates the laser receiver, outputting laser signal data and elevation data from the laser receiver; conducting time-event matching on the laser signal data obtained by the laser receiver and the point cloud data scanned by the laser radar within each scanning period of the laser radar to obtain three-dimensional coordinates of a central position of the laser receiver.

An apparatus for protecting a sensor includes: a housing accommodating the sensor to allow a sensing plane of the sensor to be exposed, and mounted on an installation object, a protective film disposed to face a sensing plane of the sensor, and a moving unit installed in the housing and moving the protective film while the protective film is maintained with respect to the sensing plane of the sensor.

In one embodiment, a computing system may transmit, using one or more light emitters, light beams of different wavelengths simultaneously into a surrounding environment. The system may determine a characteristic of the surrounding environment based on reflections of the light beams. In response to a determinization that the characteristic of the surrounding environment satisfies a criterion, the system may configure the one or more light emitters to transmit light beams of different wavelengths sequentially into the surrounding environment for measuring distances to one or more objects in the surrounding environment.

The present disclosure relates to systems and methods that facilitate a scanning light detection and ranging (LIDAR) device configured to provide an asymmetric illumination pattern. An example system includes a rotatable base configured to rotate about a first axis and a mirror assembly. The mirror assembly is configured to rotate about a second axis, which is substantially perpendicular to the first axis. The system also includes an optical cavity coupled to the rotatable base. The optical cavity includes a photodetector and a photodetector lens arranged so as to define a light-receiving axis. The optical cavity also includes a light-emitter device and a light-emitter lens arranged so as to define a light-emission axis. At least one of the light-receiving axis or the light-emission axis forms a tilt angle with respect to the first axis.

The present disclosure relates to systems and methods that facilitate a scanning light detection and ranging (LIDAR) device configured to provide an asymmetric illumination pattern. An example system includes a rotatable base configured to rotate about a first axis and a mirror assembly. The mirror assembly is configured to rotate about a second axis, which is substantially perpendicular to the first axis. The system also includes an optical cavity coupled to the rotatable base. The optical cavity includes a photodetector and a photodetector lens arranged so as to define a light-receiving axis. The optical cavity also includes a light-emitter device and a light-emitter lens arranged so as to define a light-emission axis. At least one of the light-receiving axis or the light-emission axis forms a tilt angle with respect to the first axis.

The present application is to provide a system for sensing and responding to a lateral blind spot of a mobile carrier and method thereof, which is applied for a mobile carrier during moving to a parking place. Firstly, a light scan unit and a depth image capture unit are used to scan a plurality of surrounding objects and capture a plurality of object depth images of the surrounding objects, and then a plurality of screened images are obtained according to a moving route of the mobile carrier for further obtaining correspondingly a plurality of forecasted lines to generate corresponded notice message for noting driver or ADAS. Due to the objects corresponding to the screened images and located on a blind position which is at one side of the mobile carrier, the notice message provides the driver preventing from the ignored danger by ignoring the blind position.

A computer-implemented method as well as a system for determining intensity values of pixels of distance data of the pixels generated by a simulation of a 3D scene, including an assignment of a first confidence value to each of the first initial values of the pixels and/or a second confidence value to each of the second intensity values of the pixels, and including a calculation of third, in particular corrected, intensity values of the pixels, using the confidence values assigned to each of the first intensity values and/or second intensity values. The invention also relates to a computer-implemented method for providing a trained machine learning algorithm as well as to a computer program.