Abstract: The present application discloses a data processing method and apparatus. A specific implementation of the method includes: simultaneously acquiring, by a data processing party, data to be used by a plurality of data receiving parties, and processing the to-be-used data according to processing mode information that is received in advance from each data receiving party and that indicates a processing mode for the to-be-used data, to obtain processed to-be-used data corresponding to the data receiving party; and storing the processed to-be-used data into a storage area corresponding to the data receiving party. An independent data processing party for simultaneously acquiring data that needs to be processed by each data receiving party is provided, so that the data that needs to be processed by each data receiving party is acquired at a time.

Abstract: The present application discloses a data acquisition method and apparatus for a driverless vehicle. The driverless vehicle is provided with a LIDAR sensor and a camera sensor, and the method of an embodiment comprises: acquiring a collection period of the LIDAR sensor as a first period; acquiring a start time of a current time window; executing following data processing steps: executing real-time acquiring and storing operations on data packets collected by the LIDAR sensor and the camera sensor after the start time of the current time window; and determining whether a following condition is met: the first period has elapsed from the start time of the current time window to a current time; setting the start time of the current time window to the current time in response to determining that the condition is met, and continuing executing the data processing steps.

Abstract: A motion compensation method and apparatus applicable to laser point cloud data includes acquiring laser point cloud data of a frame; using an acquisition time of a start point as a target time; interpolating coordinate transformation relations and an end laser point, to obtain coordinate transformation relations of other laser points, and transforming coordinates of the other laser points to the coordinates at the target time. During motion compensation on each frame of laser point cloud data, the coordinate transformation relations corresponding to only the start and end laser points are obtained, and the coordinate transformation relations corresponding to the two points are interpolated to obtain transformation relations corresponding to other laser points, thus performing motion compensation. Therefore, the processing speed is improved and meets high real-time requirements on systems such as autopilot control systems.

Abstract: A method and an apparatus for processing laser point cloud data includes obtaining laser point data to be used by a data receiver comprising an acquisition time; determining a timestamp for representing the acquisition time, and splitting the timestamp into a base timestamp and an offset timestamp; and storing the base timestamp and compressed laser point cloud data. Laser point cloud data output by a laser radar is compressed and comprises only offset timestamps corresponding to respective laser points. The base timestamp and the offset timestamp may be added to obtain the required synchronization precision timestamp, and the data is synchronized. The processing speed of a CPU or GPU for the laser point cloud data is improved while the timestamp precision reaches the precision required by synchronization of the laser point cloud data, and storage space is saved.

Abstract: The present application discloses a data flow processing method and apparatus for a data flow system. A specific implementation of the method includes: acquiring a to-be-processed data flow, and determining, according to a data flow processing instruction, at least one data flow processing node corresponding to the to-be-processed data flow and a passing order in which the to-be-processed data flow passes through the at least one data flow processing node; and connecting together the at least one data flow processing node according to the passing order to obtain a data flow processing channel, and importing the to-be-processed data flow to the data flow processing channel for data processing. This implementation improves the utilization of data flow processing nodes and the data flow processing efficiency.

Abstract: The present application discloses a method and an apparatus for processing point cloud data. The method of an embodiment comprises: recognizing an object in a to-be-labeled point cloud frame by using an obstacle recognition algorithm, to obtain a recognition result; presenting the recognition result as an initial labeling result of the point cloud frame; and updating the labeling result in response to a correction operation by a user on the labeling result. According to the embodiment, the speed and accuracy of point cloud data labeling are improved.

Abstract: Systems and methods are disclosed to identify entities that have a similar meaning, and may, in embodiments, be grouped into entity groups for knowledge base construction. In embodiments, the entity relations of similarity or non-similarity for an entity pair are predicted as a binary relationship. In embodiments, the prediction may be based upon similarity score between the entities and the entity features, which features are constructed using an entity feature or representation model. In embodiments, the prediction may be an iterative process involving minimum human checking and existing knowledge update. In embodiments, one or more entity groups are formed using graph search from the predicted entity pairs. In embodiments, a group centroid entity may be selected to represent each group based on one or more factors, such as its generality or popularity.

Abstract: The present application discloses a data acquiring method and apparatus applied to a driverless vehicle. A specific implementation of the method includes: selecting, from at least one laser radar of the driverless vehicle, a laser radar having a highest importance level as a first laser radar; acquiring a start time of a current time window and executing following data processing steps: executing a real-time acquisition and storage operation on point cloud data packets collected by the each of the at least one laser radar after the start time of the current time window; and determining whether any condition in a group of conditions is satisfied; and setting the start time of the current time window to be the current time and continuing to execute the data processing steps, in response to determining that any of the group of conditions is satisfied. This implementation implements the alignment and storage of point cloud data packets collected by at least one laser radar of the driverless vehicle.

Abstract: The present application discloses a method and an apparatus for processing point cloud data. The method in an embodiment comprises: presenting a to-be-labeled point cloud frame and a camera image formed by photographing an identical scene at an identical moment as the point cloud frame; determining, in response to an operation of selecting an object in the point cloud frame by a user, an area encompassing the selected object in the point cloud frame; projecting the area from the point cloud frame to the camera image, to obtain a projected area in the camera image; and adding a mark in the projected area, for labeling, by the user, the selected object in the point cloud frame according to the mark indicating an object in the camera image. This implementation can assist labeling personnel in rapidly and correctly labeling an object in a point cloud frame.

Abstract: This disclosures discloses a method and apparatus for acquiring data in a robot operating system. A specific implementation of the method includes: monitoring in real time a data storage area of an information acquirer, the information acquirer configured to acquire location state data of a driverless vehicle; obtaining updated data if the updated data are present in the data storage area; and storing the updated data into a data buffer corresponding to the information acquirer. The implementation improves the robustness of the data.

Abstract: The present application discloses a data acquisition method and apparatus for a driverless vehicle. A specific implementation of the method comprises: selecting a sensor having the highest importance level among at least one sensor of the driverless vehicle as a first sensor and at least one sensor other than the first sensor to forma second sensor set; acquiring a start time of a current time window, and executing the following data processing steps: executing real-time acquiring and storing operations on data packets collected by each sensor among the at least one sensor after the start time of the current time window; determining whether any condition in the following condition group is met; and in response to determining that any condition in the condition group is met, setting the start time of the current time window to the current time, and continuing executing the data processing steps.

Abstract: The present application discloses a method and an apparatus for processing point cloud data. The method in an embodiment comprises: presenting a to-be-labeled point cloud frame and a camera image formed by photographing an identical scene at an identical moment as the point cloud frame; determining, in response to an operation of selecting an object in the point cloud frame by a user, an area encompassing the selected object in the point cloud frame; projecting the area from the point cloud frame to the camera image, to obtain a projected area in the camera image; and adding a mark in the projected area, for labeling, by the user, the selected object in the point cloud frame according to the mark indicating an object in the camera image. This implementation can assist labeling personnel in rapidly and correctly labeling an object in a point cloud frame.

Abstract: The present application discloses a data acquiring method and apparatus applied to a driverless vehicle. A specific implementation of the method includes: selecting, from at least one laser radar of the driverless vehicle, a laser radar having a highest importance level as a first laser radar; acquiring a start time of a current time window and executing following data processing steps: executing a real-time acquisition and storage operation on point cloud data packets collected by the each of the at least one laser radar after the start time of the current time window; and determining whether any condition in a group of conditions is satisfied; and setting the start time of the current time window to be the current time and continuing to execute the data processing steps, in response to determining that any of the group of conditions is satisfied. This implementation implements the alignment and storage of point cloud data packets collected by at least one laser radar of the driverless vehicle.

Abstract: The present application discloses a data flow processing method and apparatus for a data flow system. A specific implementation of the method includes: acquiring a to-be-processed data flow, and determining, according to a data flow processing instruction, at least one data flow processing node corresponding to the to-be-processed data flow and a passing order in which the to-be-processed data flow passes through the at least one data flow processing node; and connecting together the at least one data flow processing node according to the passing order to obtain a data flow processing channel, and importing the to-be-processed data flow to the data flow processing channel for data processing. This implementation improves the utilization of data flow processing nodes and the data flow processing efficiency.

Abstract: A method and an apparatus for processing laser point cloud data includes obtaining laser point data to be used by a data receiver comprising an acquisition time; determining a timestamp for representing the acquisition time, and splitting the timestamp into a base timestamp and an offset timestamp; and storing the base timestamp and compressed laser point cloud data. Laser point cloud data output by a laser radar is compressed and comprises only offset timestamps corresponding to respective laser points. The base timestamp and the offset timestamp may be added to obtain the required synchronization precision timestamp, and the data is synchronized. The processing speed of a CPU or GPU for the laser point cloud data is improved while the timestamp precision reaches the precision required by synchronization of the laser point cloud data, and storage space is saved.

Abstract: This disclosures discloses a method and apparatus for acquiring data in a robot operating system. A specific implementation of the method includes: monitoring in real time a data storage area of an information acquirer, the information acquirer configured to acquire location state data of a driverless vehicle; obtaining updated data if the updated data are present in the data storage area; and storing the updated data into a data buffer corresponding to the information acquirer. The implementation improves the robustness of the data.

Abstract: The present application discloses a data acquisition method and apparatus for a driverless vehicle. The driverless vehicle is provided with a LIDAR sensor and a camera sensor, and the method of an embodiment comprises: acquiring a collection period of the LIDAR sensor as a first period; acquiring a start time of a current time window; executing following data processing steps: executing real-time acquiring and storing operations on data packets collected by the LIDAR sensor and the camera sensor after the start time of the current time window; and determining whether a following condition is met: the first period has elapsed from the start time of the current time window to a current time; setting the start time of the current time window to the current time in response to determining that the condition is met, and continuing executing the data processing steps.

Abstract: The present application discloses a data acquisition method and apparatus for a driverless vehicle. A specific implementation of the method comprises: selecting a sensor having the highest importance level among at least one sensor of the driverless vehicle as a first sensor and at least one sensor other than the first sensor to forma second sensor set; acquiring a start time of a current time window, and executing the following data processing steps: executing real-time acquiring and storing operations on data packets collected by each sensor among the at least one sensor after the start time of the current time window; determining whether any condition in the following condition group is met; and in response to determining that any condition in the condition group is met, setting the start time of the current time window to the current time, and continuing executing the data processing steps.

Abstract: The present application discloses a data processing method and apparatus. A specific implementation of the method includes: simultaneously acquiring, by a data processing party, data to be used by a plurality of data receiving parties, and processing the to-be-used data according to processing mode information that is received in advance from each data receiving party and that indicates a processing mode for the to-be-used data, to obtain processed to-be-used data corresponding to the data receiving party; and storing the processed to-be-used data into a storage area corresponding to the data receiving party. An independent data processing party for simultaneously acquiring data that needs to be processed by each data receiving party is provided, so that the data that needs to be processed by each data receiving party is acquired at a time.

Abstract: The present application discloses a method and an apparatus for processing point cloud data. The method of an embodiment comprises: recognizing an object in a to-be-labeled point cloud frame by using an obstacle recognition algorithm, to obtain a recognition result; presenting the recognition result as an initial labeling result of the point cloud frame; and updating the labeling result in response to a correction operation by a user on the labeling result. According to the embodiment, the speed and accuracy of point cloud data labeling are improved.