Abstract: A nanobody capable of specifically recognizing SARS-CoV-2 spike glycoprotein RBD is provided, and the nanobody comprises a CDR having an amino acid sequence selected from at least one of the following or at least 95% identical to the following: a CDR sequence of a heavy chain variable region: SEQ ID NO: 1˜21.

Abstract: The present disclosure relates to a localization method and apparatus, and a computer apparatus and a computer-readable storage medium. The localization method includes performing radar mapping and visual mapping by respectively using a radar and a vision sensor, wherein a step of the vision mapping includes determining a pose of a key frame; and combining radar localization with vision localization based on the pose of the key frame, to use vision localization results for navigation on a map obtained by the radar mapping.

Abstract: A high-definition map building method includes determining a key node describing information about a key position of a lane attribute change, determining a key node layer based on a position of the key node and an attribute of the key node, and determining a high-definition map based on a navigation map and the key node layer. The navigation map provides road-level navigation information, and the high-definition map provides lane-level navigation information.

Abstract: Disclosed are a method and an apparatus for path optimization, a robot and a storage medium. The method includes: acquiring an initial path of a robot, and iteratively optimizing the initial path until a preset iteration termination condition is met to obtain obstacle avoidance path of the robot: acquiring an iteration path corresponding to a current iteration process, determining a smoothness cost and a smoothness optimal gradient; determining a robot's footprint contour corresponding to the iteration path point, and searching for a first nearest obstacle distance; determining an obstacle cost corresponding to the iteration path and an obstacle optimal gradient corresponding to the iteration path point based on the first nearest obstacle distance; adjusting the iteration path point to acquire an iteration path corresponding to a next iteration process; inputting the smoothness cost and the obstacle cost to a preset objective function.

Abstract: A high-definition map building method includes determining a key node describing information about a key position of a lane attribute change, determining a key node layer based on a position of the key node and an attribute of the key node, and determining a high-definition map based on a navigation map and the key node layer. The navigation map provides road-level navigation information, and the high-definition map provides lane-level navigation information.