A man-machine cooperation oriented real-time posture detection method for hand-held objects

Abstract

The invention provides a man-machine cooperation oriented real-time posture detection method for hand-held objects, belonging to the technical field of a human-machine cooperation interaction system and the position and posture sensing of an industrial robot to a hand-held working object. The depth images of each part of the object to be detected are captured by a 3D stereoscopic camera, and the local point clouds are aligned and merged into a complete three-dimensional point cloud model of the object. Real-time RGB color images and depth images containing 3D point cloud information of the scene are obtained. The RGB image is segmented automatically to get the pixels representing the object in the image. The corresponding point cloud in the depth image is fused with the pixels to get the RGB-D image with color information of the object in the scene. Using ICP algorithm, the RGB-D image is matched with the complete 3D point cloud image of the object to obtain the position and posture ofthe hand-held object in the scene. The method overcomes the problem of obtaining the exact posture of the hand-held object at the current time, and can be used in a variety of scenes.

Description

technical field [0001] The invention belongs to the technical field of human-computer cooperation interaction system and industrial robot's perception of the position and posture of working objects, and relates to a real-time detection method for the position and posture of a hand-held object oriented to human-computer cooperation. Background technique [0002] Robotics is a relatively young field of modern technology that has grown across traditional engineering boundaries, covering fields such as electrical engineering, mechanical engineering, systems and industrial engineering, computer science, economics, and mathematics. In the 1960s, with the birth of the first programmable robot, the field of robotics developed rapidly. However, from the perspective of its development history, it generally passes through the following three stages. In the early stage, the first-generation robot was called a teaching robot. It mainly taught through the operator, and the internal progr...

AI Technical Summary

Problems solved by technology

The advantage of this method is high accuracy, but its application scenario is single. When changing to another scenario, it needs a lot of time and data to retrain the model (Zeng A, Yu K T, Song S, et al.Multi-view Self-supervised Deep Learning for6D Pose Estimation in the Amazon Picking Challenge[J].2016:1386-1383.)

Therefore, the above two methods are insufficient in real-time pose detection of handheld objects in the scene.

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