Monocular vision-based 2D plane grabbing method for mobile mechanical arm

Abstract

The invention discloses a monocular vision-based 2D plane grabbing method for a mobile mechanical arm. The method comprises the following steps of: calibrating internal parameters of a camera; calibrating a hand-eye relationship; establishing a standard photographing pose and a standard grabbing pose of the mechanical arm; identifying a marker by using a shape-based template matching method; solving the rotation angle of the AGV through a visual servo principle; and calculating a new grabbing pose of the mechanical arm after the AGV moves. The device of the system comprises an AGV mobile robot, a six-degree-of-freedom mechanical arm installed on the AGV, a monocular camera and a clamping jaw which are installed at the tail end of the mechanical arm, a to-be-grabbed object with a fixed position, and a marker arranged beside the to-be-grabbed object. The grabbing pose is calculated by recognizing and positioning the marker, the recognition precision is high, the stability is high, and the method can be suitable for workpieces of different shapes and textures; and meanwhile, a three-dimensional scene is degraded into a two-dimensional scene, so that the complexity and the calculation process of the problem are simplified.

Description

technical field [0001] The invention relates to the field of workpiece grasping by a mobile manipulator, in particular to a 2D plane grasping method for a mobile manipulator based on monocular vision. Background technique [0002] The mobile robotic arm combines the large-range movement capability of the automatic navigation car and the high-efficiency operation capability of the robotic arm. It breaks the inherent assembly line operation method and improves the flexibility of the production line. It is widely used in grasping, welding, rescue, handling and other work. However, due to the low positioning accuracy of the automatic navigation car, it introduces deviations to the grasping task of the manipulator. Therefore, it is of great significance to study a mobile manipulator grasping method based on machine vision technology. [0003] In terms of research on mobile manipulators, the combination of automatic navigation vehicles and industrial robots is a convenient way to ...

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Problems solved by technology

[0005] In view of the above-mentioned defects of the prior art, the problem to be solved by the present invention is that the positioning accuracy of the autonomous navigation car is low, the positioning using visual recognition is difficult, the stability is poor, and the problem is limited by factors such as the shape and color of the workpiece.

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