Autonomously driven vehicles operate in rain, snow and other adverse weather conditions. An on-board vehicle sensor has a beam with a diameter that is only intermittently blocked by rain, snow, dust or other obscurant particles. This allows an obstacle detection processor is to tell the difference between obstacles, terrain variations and obscurant particles, thereby enabling the vehicle driving control unit to disregard the presence of obscurant particles along the route taken by the vehicle. The sensor may form part of a LADAR or RADAR system or a video camera. The obstacle detection processor may receive time-spaced frames divided into cells or pixels, whereby groups of connected cells or pixels and/or cells or pixels that persist over longer periods of time are interpreted to be obstacles or terrain variations. The system may further including an input for receiving weather-specific configuration parameters to adjust the operation of the obstacle detection processor.

A measuring device can have a scanning functionality for optical surveying of an environment, wherein the measuring device has a sensor comprising an assembly of microcells as a receiving surface and direction-dependent active sections of the receiver are defined depending on the transmission direction of the transmitted radiation, in order to adapt the active receiver surface to a varying imaging position of the received radiation.

An optical measuring device having a base for placing the measuring device and a targeting unit that is rotatable with respect to the base and defines a target axis for targeting a target object that is to be measured. The targeting unit has a first beam path for emitting optical measurement radiation in the direction of the target object that is to be measured. The targeting unit furthermore has a diffractive optical element (DOE), which is arranged or arrangeable in the beam path such that the optical measurement radiation is homogenized.

A laser detection and ranging system and method for operating thereof. In some embodiments, the method includes: transmitting a plurality of laser pulses, each at a respective one of a plurality of pulse transmission times; detecting a plurality of return pulses, each at a respective one of a plurality of return pulse times; and estimating a range or a range rate of a target based on the pulse transmission times and the return pulse times. Each of the pulse transmission times may be offset from a corresponding nominal pulse transmission time by a respective pulse position modulation offset, the nominal pulse transmission times being uniformly spaced with a period corresponding to a pulse repetition frequency, the pulse repetition frequency being greater than 500 kHz.

Example embodiments relate to selective deactivation of light emitters for interference mitigation in light detection and ranging (lidar) devices. An example method includes deactivating one or more light emitters within a lidar device during a firing cycle. The method also includes identifying whether interference is influencing measurements made by the lidar device. Identifying whether interference is influencing measurements made by the lidar device includes determining, for each light detector of the lidar device that is associated with the one or more light emitters deactivated during the firing cycle, whether a light signal was detected during the firing cycle.

Sensors, including time-of-flight sensors, may be used to detect objects in an environment. In an example, a vehicle may include a time-of-flight sensor that images objects around the vehicle, e.g., so the vehicle can navigate relative to the objects. Sensor data generated by the time-of-flight sensor can return unreliable pixels, e.g., in the case of over- or under-exposure. In some examples, parameters associated with power of a time-of-flight sensor can be altered based on a number of unreliable pixels in measured data and/or based on intensity values of the measured data. For example, unreliable pixels can be determined using phase frame information captured at a receiver of the sensor.

A photodetector includes a plurality of channels each having a plurality of SPAD units, each SPAD unit having an avalanche photodiode. The photodetector is capable of selecting outputting or non-outputting of the channels. The SPAD unit includes: an active quenching circuit which performs active quenching of the avalanche photodiode; and a control circuit which brings the active quenching circuit which corresponds to the channel where non-outputting is selected into an operable state.

A method and system for automatically processing point cloud based on reinforcement learning are provided. The method for automatically processing point cloud based on reinforcement learning according to an embodiment of the present disclosure includes scanning to collect a point cloud (PCL) and an image through a lidar and a camera; calibrating, by a controller, to match locations of the image and the point cloud through reinforcement learning that maximizes a reward including geometric and luminous intensity consistency of the image and the point cloud; and meshing, by the controller, the point cloud into a 3D image through reinforcement learning that minimizes a reward including a difference between a shape of the image and a shape of the point cloud.

A method, apparatus, and system for estimating a moving speed of a detected pedestrian at an autonomous driving vehicle (ADV) is disclosed. A pedestrian is detected in a plurality of frames of point clouds generated by a LIDAR device installed at an autonomous driving vehicle (ADV). In each of at least two of the plurality of frames of point clouds, a minimum bounding box enclosing points corresponding to the pedestrian excluding points corresponding to limbs of the pedestrian is generated. A moving speed of the pedestrian is estimated based at least in part on the minimum bounding boxes across the at least two of the plurality of frames of point clouds. A trajectory for the ADV is planned based at least on the moving speed of the pedestrian. Thereafter, control signals are generated to drive the ADV based on the planned trajectory.

A distance measuring device of the present disclosure includes a light source section that irradiates a subject with light, a light receiving device that receives reflected light from the subject, and an application processor that controls the light source section and the light receiving device. The light receiving device has an object detection function of measuring a distance to the subject to detect that the subject approaches within a predetermined distance, and provides notification of a detection result to the application processor in a standby state. The application processor starts up in response to the notification from the light receiving device.