Grasping detection method of service robot based on dual-channel convolutional neural network

Abstract

The invention belongs to the technical field of service robots, and specifically relates to a method, system, and device for grasping and detecting service robots based on a dual-channel convolutional neural network, aiming at solving the problem that it is difficult for a robot grasping and detecting method to be both real-time and accurate. The method of the present invention includes: acquiring an original color image and an original depth image of the surrounding environment, and converting the original color image into an original grayscale image; acquiring a bounding frame of a target object, and obtaining a first depth image area and a first grayscale image area; Adjust the image area to the set size; encode the resized image area and add it; decode the added feature map to obtain the capture quality feature map, width feature map, height feature map, and first angle Feature map, second angle feature map; get the best grabbing rectangle and its corresponding best grabbing detection frame in the original color image, and realize the grabbing detection of the target object. The invention ensures the real-time and accuracy of grabbing.

Description

technical field [0001] The invention belongs to the technical field of service robots, and in particular relates to a method, system and device for grasping and detecting a service robot based on a dual-channel convolutional neural network. Background technique [0002] In recent years, with the rapid development of artificial intelligence, sensing technology, computing processing technology, etc., service robots have gradually entered people's daily life. Among them, service robots equipped with mechanical arms are popular because they can provide object grabbing services. focus on. In order to grasp the target object, the robot needs to first use deep learning-based object detection methods (such as Faster R-CNN, YOLO, SSD, etc.) to detect the target object, and then determine the best capture of the target object in the image The detection frame, and then guide the robotic arm to carry out the grasping operation, in which determining the best grasping detection frame of ...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above problems in the prior art, that is, in order to solve the problem that the existing robot grasping detection method is difficult to have good real-time performance and good accuracy at the same time, the present invention proposes a method based on dual-channel convolution A neural network service robot grasping detection method, the method comprising:

Images