Abstract: Systems and methods for the simultaneous localization and mapping of autonomous vehicle systems are provided. A method includes receiving a plurality of input image frames from the plurality of asynchronous image devices triggered at different times to capture the plurality of input image frames. The method includes identifying reference image frame(s) corresponding to a respective input image frame by matching the field of view of the respective input image frame to the fields of view of the reference image frame(s). The method includes determining association(s) between the respective input image frame and three-dimensional map point(s) based on a comparison of the respective input image frame to the one or more reference image frames. The method includes generating an estimated pose for the autonomous vehicle the one or more three-dimensional map points. The method includes updating a continuous-time motion model of the autonomous vehicle based on the estimated pose.

Abstract: A traveling rail jointing device for a pivot-type suspended monorail multi-way turnout beam includes: a jointing plate, a rotating support seat, a lever and a push-pull assembly. The jointing plate is disposed with a rotation shaft thereon along an extension direction of a plate surface thereof. The rotation shaft is rotatably embedded on the rotating support seat. A first end of the lever is fixed on the jointing plate, and a second end of the lever is connected to the push-pull assembly. The technical solution of the disclosure can realize reliable jointing for pivot-type suspended monorail multi-way turnout beams through a simple structure.

Abstract: Disclosed herein are systems and method including a method for managing an autonomous vehicle. The method includes obtaining labels associated with various aspects of right-of-way interactions between an autonomous vehicle and an agent, wherein the right-of-way interactions occur when a human driver takes over for the autonomous vehicle and performs the right-of-way interactions, running an autonomous vehicle stack that is untrained for processing right-of-way interactions between the autonomous vehicle and the agent, injecting the labels into the autonomous vehicle stack and determining, based on the injecting of the labels into the autonomous vehicle stack, a performance of the autonomous vehicle stack.

Abstract: An aerial transfer carriage and a control method therefor. The aerial transfer carriage includes: a carriage frame, a spreader, a lifting device and an anti-sway device. The anti-sway device includes two correction winch mechanisms and two correction ropes. The lifting device drives an end of each of the two correction ropes to be reel and unreel. The two correction winch mechanisms respectively drive another end of each of the two correction ropes to be reel and unreel. When it is required to correct a deflection of the spreader, the two opposite ends of the correction rope are wound or unwound respectively, and with the two correction ropes disposed crosswise, the correction rope adjusts a lateral position and a longitudinal position of the spreader during reel and unreel.

Abstract: An auxiliary switching device of pivot-type suspended monorail multi-way turnout system includes: a first driving member, a bracket, a slide block, a slide rail, a second driving member and a switching push head. An action end of the first driving member is connected to the bracket to drive the bracket to move back and forth along a first axial direction. The slide block is disposed on the bracket, and the slide block is slidably connected onto the slide rail. The second driving member is disposed on the bracket. The switching push head is connected to an action end of the second driving member.

Abstract: Provided are an emergency treatment system, an emergency treatment method, and an electronic device. The emergency treatment system includes: an information collection terminal, which is deployed in a rescue vehicle and is used for collecting medical data of a subject to be treated and uploading the medical data to a data lake cluster; the data lake cluster, which is used for performing data access, data processing, data storage and data distribution on the medical data of said object; and a medical business system, which is used for acquiring the medical data of said object from the data lake cluster.

Abstract: Systems and methods for the simultaneous localization and mapping of autonomous vehicle systems are provided. A method includes receiving a plurality of input image frames from the plurality of asynchronous image devices triggered at different times to capture the plurality of input image frames. The method includes identifying reference image frame(s) corresponding to a respective input image frame by matching the field of view of the respective input image frame to the fields of view of the reference image frame(s). The method includes determining association(s) between the respective input image frame and three-dimensional map point(s) based on a comparison of the respective input image frame to the one or more reference image frames. The method includes generating an estimated pose for the autonomous vehicle the one or more three-dimensional map points. The method includes updating a continuous-time motion model of the autonomous vehicle based on the estimated pose.

Abstract: The present disclosure generally relates to autonomous vehicle (AV) navigation and, more specifically, to improving AV determinations regarding when to yield to other vehicles (entities) in various driving scenarios. In some aspects, a process of the disclosed technology includes steps for receiving road data comprising sensor data collected by an autonomous vehicle (AV), extracting trajectory data from the road data, for each of the one or more entities, and providing the trajectory data to a machine-learning (ML) model, wherein the ML model is trained to generate a yield prediction for each of the one or more entities. In some aspects, the process can further include steps for determining a path for the AV based on the yield prediction for each of the one or more entities. Systems and machine-readable media are also provided.

Abstract: Aspects of the disclosed technology provide solutions for evaluating the performance of a yield prediction model that is used to inform path planning decisions made by a planning module of an autonomous vehicle (AV) software stack. In some aspects, a process of the disclosed technology includes steps for receive legacy road data, extracting AV plan information from the legacy road data, the AV plan information comprising an original path selected by the AV for navigating through the environment, and providing the legacy road data to a yield prediction model to generate a yield prediction for each of the one or more entities in the environment. In some aspects, the process can further include steps for determining an alternate path based on the yield prediction for each of the one or more entities, and evaluating the yield prediction model based on the original path selected by the AV and the alternate path. Systems and machine-readable media are also provided.

Abstract: Aspects of the disclosed technology provide solutions for evaluating the performance of a planning module (or planning layer) of an autonomous vehicle (AV) software stack. In some aspects, a process of the disclosed technology can include steps for receiving road data comprising sensor data collected by an autonomous vehicle (AV), providing the road data to a planning module of the AV to determine a yield projection for each of the one or more entities, and providing the road data to a yield prediction model to determine a yield prediction for each of the one or more entities. In some aspects, the process can further include steps for evaluating a performance of the planning module of the AV based on the yield projection for each of the one or more entities and the yield prediction for each of the one or more entities. Systems and machine-readable media are also provided.

Abstract: The present disclosure provides an emergency alarm processing method and an emergency alarm processing system. The emergency alarm processing method includes: receiving an emergency access request; according to the access means of the emergency access request, storing the emergency access request into subqueues of a unified queuing queue, wherein the unified queuing queue includes at least two subqueues, each of the subqueues is used for storing the emergency access request of at least one access means, and the access means of the emergency access request stored in each of the subqueues are different; allocating an emergency access request in the unified queuing queue to a target alarm dispatching seat supporting a corresponding access means.

Abstract: The present application discloses a dispatching and control cloud data processing method, device and system. The method includes the following operations: pilot node device acquires a global scheduling task, decomposes the global scheduling task to obtain scheduling tasks, issues the scheduling tasks to collaborative node device, acquires data collection ranges and data processing rules of the collaborative node devices, and delivers them to the collaborative node devices; the collaborative node devices receive and execute the scheduling tasks issued by the pilot node device; receives the data collection ranges and the data processing rules issued by the pilot node device, acquires, based on the scheduling tasks, collected data in the data collection ranges, processes the acquired collected data according to the data processing rules to obtain the processed data, uploads the processed data to the pilot node device; the pilot node device receives the processed data uploaded by the collaborative node devices.

Abstract: The present invention discloses a method and system for recognizing a geometric regularity image of a honeycomb structure. The method includes the steps of image acquisition, image processing, vertex extraction, cell reconstruction, and quality evaluation, wherein a step of binaryzation is set between the step of image processing and the step of vertex extraction, and is to set a pixel value of a background in the image to be 0 and set a pixel value of a honeycomb skeleton in the image to be 1 to form a binary image, and the step of quality evaluation is to calculate angular deviation values of all the cells and an average thereof as well as linear deviation values and an average thereof based on the reconstructed cell image, and determine whether the honeycomb structure is qualified or not by comparing with a set tolerance zone.

Abstract: Disclosed are a method for evaluating a geometric form of a honeycomb product and a system for detecting and evaluating a geometric form of a honeycomb product. The method for evaluating the geometric form includes: acquiring a top-surface image and a side-surface image of the honeycomb product; acquiring vertex coordinates by extracting vertices from the top-surface image; acquiring serial numbers of six vertices of each cell by reconstructing the cells of the top-surface image; computing deviation angles of six interior angles of each cell based on the serial numbers and vertex coordinates of the six vertices of each cell; extracting a top-surface side boundary and a side-surface side boundary of the honeycomb product from the top-surface image and the side-surface image; computing a maximum top-surface deflection and a maximum side-surface deflection of the honeycomb product based on the top-surface side boundary and the side-surface side boundary.

Abstract: A method and apparatus for checking power grid measurement data, a device, a storage medium and a program product. The method includes: a feature factor of power grid measurement data is extracted; power balance of a set time scale is checked based on the measurement data and the feature factor to obtain a check result; a classification rule base of abnormal problems of measurement data is built based on the check result; and an abnormal problem in target measurement data is checked based on the classification rule base of abnormal problems of measurement data, to obtain a measurement data quality report.

Abstract: The disclosure relates to an aerial transportation vehicle including a vehicle frame.

Abstract: Disclosed are a method for evaluating a geometric form of a honeycomb product and a system for detecting and evaluating a geometric form of a honeycomb product. The method for evaluating the geometric form includes: acquiring a top-surface image and a side-surface image of the honeycomb product; acquiring vertex coordinates by extracting vertices from the top-surface image; acquiring serial numbers of six vertices of each cell by reconstructing the cells of the top-surface image; computing deviation angles of six interior angles of each cell based on the serial numbers and vertex coordinates of the six vertices of each cell; extracting a top-surface side boundary and a side-surface side boundary of the honeycomb product from the top-surface image and the side-surface image; computing a maximum top-surface deflection and a maximum side-surface deflection of the honeycomb product based on the top-surface side boundary and the side-surface side boundary.

Abstract: The present invention discloses a method and system for recognizing a geometric regularity image of a honeycomb structure. The method includes the steps of image acquisition, image processing, vertex extraction, cell reconstruction, and quality evaluation, wherein a step of binaryzation is set between the step of image processing and the step of vertex extraction, and is to set a pixel value of a background in the image to be 0 and set a pixel value of a honeycomb skeleton in the image to be 1 to form a binary image, and the step of quality evaluation is to calculate angular deviation values of all the cells and an average thereof as well as linear deviation values and an average thereof based on the reconstructed cell image, and determine whether the honeycomb structure is qualified or not by comparing with a set tolerance zone.

Abstract: Disclosed herein are systems and method including a method for managing an autonomous vehicle. The method includes obtaining labels associated with various aspects of right-of-way interactions between an autonomous vehicle and an agent, wherein the right-of-way interactions occur when a human driver takes over for the autonomous vehicle and performs the right-of-way interactions, running an autonomous vehicle stack that is untrained for processing right-of-way interactions between the autonomous vehicle and the agent, injecting the labels into the autonomous vehicle stack and determining, based on the injecting of the labels into the autonomous vehicle stack, a performance of the autonomous vehicle stack.

Abstract: Disclosed herein are systems and method including a method for managing an autonomous vehicle. The method include running an autonomous vehicle that performs right-of-way movements relative to agents, recording, for a plurality of segments of time or distance, where the autonomous vehicle and where the agents are for each tick in each of the plurality of segments, running an autolabeler module on a segment of the plurality of segments to calculate a respective value for each of a plurality of right-of-way labels and using the plurality of right-of-way labels to perform one or more of spoofing an autonomous vehicle stack or to train a right-of-way machine learning model.