Robot grabbing pose estimation method combining geometric constraint

A pose estimation and geometric constraint technology, applied in the direction of manipulators, program-controlled manipulators, manufacturing tools, etc., can solve the problems affecting the real-time performance of grasping detection and the lack of generalization performance of traditional methods, so as to achieve applicability and high computational efficiency Effect

Active Publication Date: 2020-01-07
NORTHEASTERN UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the wide variety of objects, different shapes and postures and irregularities in unstructured environments such as home environments, traditional methods lack good generalization performance
Those skilled in the art study the feature information of the target object based on the RGBD...

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  • Robot grabbing pose estimation method combining geometric constraint
  • Robot grabbing pose estimation method combining geometric constraint
  • Robot grabbing pose estimation method combining geometric constraint

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Embodiment Construction

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only for illustration, and are not intended to limit the present application.

[0030] The experimental environment is the Kinetic version of ROS, based on the Ubuntu 16.04 operating system, and the computer configuration is Intel(R) Core(TM) i7 2.6GHz, 16GB RAM. Such as figure 1 As shown, the robot used in the example of the present invention is a Jaco robot, and the RGB-D camera used is Intel(R) RealSence SR300. The camera is installed at the end of the robot to form an eye-in-hand system. The target objects to be detected are all common objects in the home environment, and are placed in the area to be grasped on the test bench. Through the method for estimating the grasping pose of the target object described in the ...

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Abstract

The invention relates to a robot grabbing pose estimation method combining geometric constraint and belongs to the technical field of robot vision grabbing. The robot grabbing pose estimation method combining geometric constraint comprises the following steps: generating an initial grabbing pose by means of holder simplified shape constraint to generate a grabbing sample containing a stable grabbing pose; and then screening a semi-stable grabbing pose quickly through force closed constraint, then analyzing the semi-stable grabbing pose by means of force balancing constraint and estimating thestable grabbing pose of a target object. The robot grabbing pose estimation method combining geometric constraint is suitable for estimating the grabbing poses of different objects and can estimate the stable grabbing pose within one second, and is high in calculating efficiency. Parameters of the holder in an algorithm are changed and the algorithm can be applied to other types of holders, so that the algorithm is applicable.

Description

technical field [0001] The invention belongs to the technical field of robot visual grasping, and in particular relates to a robot grasping pose estimation method based on multiple geometric constraints. Background technique [0002] In recent years, the continuous development of computer vision and robotics has promoted the integration of home service robots into human life. In addition to positioning and navigation, the home service robot grasps the object is the premise for the robot to provide high-quality services for human beings. Robots use visual information to quickly and stably detect the grasping pose of an object, and then operate the object according to the grasping pose is a commonly used method at present. [0003] The traditional robot grasping method is to establish an object grasping pose data set, and then perform matching based on templates. The size, accuracy and computer resources of the model library directly affect the quality of grasping pose estima...

Claims

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Application Information

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IPC IPC(8): B25J9/16
CPCB25J9/1697B25J9/1664B25J9/1602
Inventor 张云洲苏杰李奇刘灏徐文娟
Owner NORTHEASTERN UNIV
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