Abstract: The present disclosure relates to systems and methods that facilitate light detection and ranging operations. An example method includes determining, for at least one light-emitter device of a plurality of light-emitter devices, a light pulse schedule. The plurality of light-emitter devices is operable to emit light along a plurality of emission vectors. The light pulse schedule is based on a respective emission vector of the at least one light-emitter device and a three-dimensional map of an external environment. The light pulse schedule includes at least one light pulse parameter and a listening window duration. The method also includes causing the at least one light-emitter device of the plurality of light-emitter devices to emit a light pulse according to the light pulse schedule. The light pulse interacts with an external environment.

Abstract: Systems and methods for performing operations based on LIDAR communications are described. An example device may include one or more processors and a memory coupled to the one or more processors. The memory includes instructions that, when executed by the one or more processors, cause the device to receive data associated with a modulated optical signal emitted by a transmitter of a first LIDAR device and received by a receiver of a second LIDAR device coupled to a vehicle and the device, generate a rendering of an environment of the vehicle based on information from one or more LIDAR devices coupled to the vehicle, and update the rendering based on the received data. Updating the rendering includes updating an object rendering of an object in the environment of the vehicle. The instructions further cause the device to provide the updated rendering for display on a display coupled to the vehicle.

Abstract: Computing devices, systems, and methods described in various embodiments herein may relate to light detection and ranging (LIDAR or lidar) systems. An example computing device could include a controller having at least one processor and at least one memory. The at least one processor is configured to execute program instructions stored in the at least one memory so as to carry out operations. The operations include receiving information indicative of transmit light emitted from a lidar system along a light-emission axis. The operations also include determining, based on the received information, a maximum instrumented distance. The maximum instrumented distance includes a known unobstructed region defined by a ray segment extending between the lidar system and a point along the light-emission axis.

Abstract: A computing system may operate a LIDAR device to emit and detect light pulses in accordance with a time sequence including standard detection period(s) that establish a nominal detection range for the LIDAR device and extended detection period(s) having durations longer than those of the standard detection period(s). The system may then make a determination that the LIDAR detected return light pulse(s) during extended detection period(s) that correspond to particular emitted light pulse(s). Responsively, the computing system may determine that the detected return light pulse(s) have detection times relative to corresponding emission times of particular emitted light pulse(s) that are indicative of one or more ranges. Given this, the computing system may make a further determination of whether or not the one or more ranges indicate that an object is positioned outside of the nominal detection range, and may then engage in object detection in accordance with the further determination.

Abstract: A snapshot of a bucket is generated that includes corresponding object versions of objects stored in the bucket. A read-only copy of the bucket is generated using the snapshot that includes the corresponding object versions of the objects. The generation of the read-only copy of the bucket prevents deletion of the snapshot.

Abstract: The present disclosure relates to systems and methods that facilitate light detection and ranging operations. An example method includes determining, for at least one light-emitter device of a plurality of light-emitter devices, a light pulse schedule. The plurality of light-emitter devices is operable to emit light along a plurality of emission vectors. The light pulse schedule is based on a respective emission vector of the at least one light-emitter device and a three-dimensional map of an external environment. The light pulse schedule includes at least one light pulse parameter and a listening window duration. The method also includes causing the at least one light-emitter device of the plurality of light-emitter devices to emit a light pulse according to the light pulse schedule. The light pulse interacts with an external environment.

Abstract: One example system comprises a LIDAR sensor that rotates about an axis to scan an environment of the LIDAR sensor. The system also comprises one or more cameras that detect external light originating from one or more external light sources. The one or more cameras together provide a plurality of rows of sensing elements. The rows of sensing elements are aligned with the axis of rotation of the LIDAR sensor. The system also comprises a controller that operates the one or more cameras to obtain a sequence of image pixel rows. A first image pixel row in the sequence is indicative of external light detected by a first row of sensing elements during a first exposure time period. A second image pixel row in the sequence is indicative of external light detected by a second row of sensing elements during a second exposure time period.

Abstract: In a method for optically measuring technical surfaces using a confocal sensor, light is directed onto a sample surface to be measured via an optical system that contains an illumination mask, a sensor matrix, a beam splitter for combining illumination beam and detection beam paths, and imaging optics. The mask has transparent and non-transparent or slightly transparent regions arranged in a checkerboard pattern. The pitch of the mask pattern corresponds to the pixel pitch of the matrix. The mask and the matrix are adjusted relative to each other such that the transparent regions and the pixels of the matrix are simultaneously sharply imaged onto the sample by the imaging optics, whereby the sharp image of the mask is then sharply imaged onto the matrix so that a checkerboard pattern of light and dark illuminated pixels is produced on the matrix. The transparent regions of the mask are round.

Abstract: A liquid level sensing system for a vehicle tank may include a liquid level display including a display panel and a first number of visual indicators carried by the display panel. The system may also include capacitive sensors to be coupled to the vehicle tank to sense a second number of possible liquid levels being greater than the first number of visual indicators. In addition, the system may include a controller configured to drive the visual indicators in a modulation pattern based upon the capacitive sensors to thereby display a sensed liquid level having a resolution corresponding to the second number of possible liquid levels.

Abstract: Media input audio data corresponding to a media stream and microphone input audio data from at least one microphone may be received. A first level of at least one of a plurality of frequency bands of the media input audio data, as well as a second level of at least one of a plurality of frequency bands of the microphone input audio data, may be determined. Media output audio data and microphone output audio data may be produced by adjusting levels of one or more of the first and second plurality of frequency bands based on the perceived loudness of the microphone input audio data, of the microphone output audio data, of the media output audio data and the media input audio data. One or more processes may be modified upon receipt of a mode-switching indication.

Abstract: A storage system stores objects in a bucket at a storage device of the storage system. Each of the objects has a corresponding version. A processing device generates a snapshot of the bucket. The snapshot captures the corresponding version of each of the objects at a time associated with the generation of the snapshot.

Abstract: A method of determining service provider appointments is provided. The method can include providing, by a data processor of a multi-provider scheduling platform, at least one conversational agent configured to receive query inputs and generate response outputs associated with scheduling target assignments performed by at least one service provider. First data characterizing a query input provided to the at least one conversational agent can be received. The query input can include a request for at least one service provider to perform target assignment at a target assignment time. Second data characterizing a response output contextually relevant to the query input can be determined. The response output can include one or more appointments corresponding to the target assignment and the target assignment time and the response output including the one or more appointments can be provided to the conversational agent. Related systems and computer program products are also provided.

Abstract: One example system comprises a LIDAR sensor that rotates about an axis to scan an environment of the LIDAR sensor. The system also comprises one or more cameras that detect external light originating from one or more external light sources. The one or more cameras together provide a plurality of rows of sensing elements. The rows of sensing elements are aligned with the axis of rotation of the LIDAR sensor. The system also comprises a controller that operates the one or more cameras to obtain a sequence of image pixel rows. A first image pixel row in the sequence is indicative of external light detected by a first row of sensing elements during a first exposure time period. A second image pixel row in the sequence is indicative of external light detected by a second row of sensing elements during a second exposure time period.

Abstract: The present invention relates to the technical field of automatically determining the content of images. In particular, the present invention relates to a process for assigning images to predefined categories depending on their content. Subject matter of the present invention is a computer-implemented method of automatically determining to which part of an object the content depicted in one or more images belongs to, a computer system configured to execute the computer-implemented method, and a non-transitory computer-readable storage medium comprising processor-executable instructions with which to perform the computer-implemented method.

Abstract: The techniques described herein relate to a systems and methods for a digital asset generation platform. The digital asset generation platform may ingest an ingest input. The digital asset generation platform may utilize a document identification engine corresponding to a first stage of a multi-stage convolutional neural network for identifying document types of documents. The digital asset generation platform may utilize an object detector engine corresponding to a second stage of the multi-stage convolutional neural network for detecting a dynamic mapping in the digital file. The digital asset generation platform may utilize a post-processing engine for classifying the dynamic mapping in the at least one digital file. The digital asset generation platform may dynamically generate a digital asset representative of the document based on the key value data pairs extracted from the dynamic mapping.

Abstract: Embodiments are provided for managing the operation of sensors in an electronic device. According to certain aspects, the electronic device may detect a change in motion from a set of lower-sensitivity sensor data generated by a sensor(s) operating in a lower-sensitivity mode. When the change in motion is detected and during a timeout window, the sensor(s) may generate an additional set of lower-sensitivity sensor data and a set of higher-sensitivity sensor data. The electronic device may initially confirm the change in motion based on analyzing the set of higher-sensitivity sensor data. Further, the electronic device may determine that the additional set of lower-sensitivity does not indicate an additional change in motion, and may deem the confirmation of the change in motion as a false positive.

Abstract: The present disclosure relates to systems and methods involving Light Detection and Ranging (LIDAR or lidar) systems. Namely, an example method includes causing a light source of a LIDAR system to emit light along an emission vector. The method also includes adjusting the emission vector of the emitted light and determining an elevation angle component of the emission vector. The method further includes dynamically adjusting a per pulse energy of the emitted light based on the determined elevation angle component. An example system includes a vehicle and a light source coupled to the vehicle. The light source is configured to emit light along an emission vector toward an environment of the vehicle. The system also includes a controller operable to determine an elevation angle component of the emission vector and dynamically adjust a per pulse energy of the emitted light based on the determined elevation angle component.

Abstract: 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.

Abstract: A computing system may operate a LIDAR device to emit and detect light pulses in accordance with a time sequence including standard detection period(s) that establish a nominal detection range for the LIDAR device and extended detection period(s) having durations longer than those of the standard detection period(s). The system may then make a determination that the LIDAR detected return light pulse(s) during extended detection period(s) that correspond to particular emitted light pulse(s). Responsively, the computing system may determine that the detected return light pulse(s) have detection times relative to corresponding emission times of particular emitted light pulse(s) that are indicative of one or more ranges. Given this, the computing system may make a further determination of whether or not the one or more ranges indicate that an object is positioned outside of the nominal detection range, and may then engage in object detection in accordance with the further determination.