Abstract: The present disclosure generally relates to a system of a delivery device for combining sensor data from various types of sensors to generate a map that enables the delivery device to navigate from a first location to a second location to deliver an item to the second location. The system obtains data from RGB, LIDAR, and depth sensors and combines this sensor data according to various algorithms to detect objects in an environment of the delivery device, generate point cloud and pose information associated with the detected objects, and generates object boundary data for the detected objects. The system further identifies object states for the detected object and generates the map for the environment based on the detected object, the generated object proposal data, the labeled point cloud data, and the object states. The generated map may be provided to other systems to navigate the delivery device.

Abstract: The present disclosure relates to the combination of IN10018 and an epidermal growth factor receptor tyrosine kinase inhibitor for the treatment of tumors.

Abstract: This application discloses a processing node management method and apparatus, a device, and a storage medium, which belongs to the field of cloud technologies and big data.

Abstract: The present disclosure generally relates to a system of a delivery device for combining sensor data from various types of sensors to generate a map that enables the delivery device to navigate from a first location to a second location to deliver an item to the second location. The system obtains data from RGB, LIDAR, and depth sensors and combines this sensor data according to various algorithms to detect objects in an environment of the delivery device, generate point cloud and pose information associated with the detected objects, and generates object boundary data for the detected objects. The system further identifies object states for the detected object and generates the map for the environment based on the detected object, the generated object proposal data, the labeled point cloud data, and the object states. The generated map may be provided to other systems to navigate the delivery device.

Abstract: An autonomous delivery robot system to enable delivery of a product to a customer is described. One autonomous ground vehicle (AGV) includes a processing device that receives a delivery request comprising a route divided into multiple navigation segments and computes a navigable space from perception data stored in a perception map. The perception map is a robot-centered local map that stores the perception data indicative of the surroundings of the AGV. The processing device computes a cost inflation from the perception data stored in the perception map, determines a sub-goal that is on the navigable space and reachable by the AGV using the navigable space and the cost inflation, and determines a path to achieve the sub-goal using the using the navigable space and the cost inflation. The processing device controls one or more actuators to move along the path.

Abstract: The various embodiments described herein include methods, systems, and devices for invoking an interface for a hybrid cloud. In one aspect, a computing system receives, from an invoker, an interface invocation request for a hybrid cloud, the request including a uniform resource locator address and information of a first target cloud platform. In accordance with the request, the computing system determines an interface of the first target cloud platform, e.g., a type of the first target cloud platform, a region of the interface of the first target cloud platform; and an interface within the region as the interface of the first target cloud platform. Next, the computing system sends the request to the interface of the first target cloud platform and then receives a response from the interface of the first target cloud platform.

Abstract: The various embodiments described herein include methods, systems, and devices for invoking an interface for a hybrid cloud. In one aspect, a computing system receives, from an invoker, an interface invocation request for a hybrid cloud, the request including a uniform resource locator address and information of a first target cloud platform. In accordance with the request, the computing system determines an interface of the first target cloud platform, e.g., a type of the first target cloud platform, a region of the interface of the first target cloud platform; and an interface within the region as the interface of the first target cloud platform. Next, the computing system sends the request to the interface of the first target cloud platform and then receives a response from the interface of the first target cloud platform.

Abstract: Image classification and related imaging tasks performed using machine learning tools may be accelerated by using one or more of such tools to associate an image with a cluster of such labels or categories, and then to select one of the labels or categories of the cluster as associated with the image. The clusters of labels or categories may comprise labels that are mutually confused for one another, e.g., two or more labels or categories that have been identified as associated with a single image. By defining clusters of labels or categories, and configuring a machine learning tool to associate an image with one of the clusters, processes for identifying labels or categories associated with images may be accelerated because computations associated with labels or categories not included in the cluster may be omitted.