Detection method and device, computer equipment and storage medium

Abstract

The invention provides a detection method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining first point cloud data in a target environment and target geometric features of a target object; screening first target point cloud data belonging to the target object from the first point cloud data based on the target geometric feature, and performing object segmentation on the first point cloud data except the first target point cloud data to obtain second target point cloud data of other objects except the target object; based on the second target point cloud data and the first target point cloud data, determining position relation information between each other object and the target object; and based on the position relation information, screening a first obstacle which is located on the target object and exceeds the target object by at least a preset distance from other objects. According to the embodiment of the invention, the first target point cloud data of the target object and the second target point cloud data of other objects can be accurately segmented by using the target geometric features, so that the first obstacle can be accurately distinguished.

Description

technical field [0001] The present disclosure relates to the technical field of point cloud processing and object detection, and in particular, to a detection method, device, computer equipment and storage medium. Background technique [0002] When the robot is running in a narrow shelf lane, some goods on the shelves on both sides of the robot that exceed the shelf will collide with the robot, affecting the normal operation of the robot. Usually, the volume of the excess part of the goods is small, and the excess part of the goods is closely connected with the shelf. By clustering the collected point cloud data, it is impossible to segment the excess part of the goods with a smaller volume that is closely connected with the shelf. It is believed that the excess part of the goods is integrated with the shelf, so accurate segmentation cannot be achieved, resulting in a decrease in the robot's environmental perception, and the inability to complete accurate obstacle avoidance....

AI Technical Summary

Problems solved by technology

[0002] When the robot is running in a narrow shelf lane, some goods on the shelves on both sides of the robot that exceed the shelf will collide with the robot, affecting the normal operation of the robot

Usually, the volume of the excess part of the goods is small, and the excess part of the goods is closely connected with the shelf. By clustering the collected point cloud data, it is impossible to segment the excess part of the goods with a smaller volume that is closely connected with the shelf. It is believed that the excess part of the goods is integrated with the shelf, so accurate segmentation cannot be achieved, resulting in a decrease in the robot's environmental perception, and the inability to complete accurate obstacle avoidance. In the event of a collision, the robot is easily damaged and the maintenance cost of the robot is increased.

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