Method and system for grabbing with a robotic arm

Abstract

The invention provides a mechanical arm grabbing method and a system for achieving the method. The method comprises the following steps that S1, point cloud information of the surface (the surface capable of being seen in the view field of a camera) of an object to be grabbed is collected; S2, data of the point cloud information is further processed, and feasible grabbing points meeting constraintconditions are extracted through a grabbing programming algorithm; S3, the grabbing points are adopted as inverse kinematics input of a mechanical arm, and a motion control instruction is sent to themechanical arm and a two-finger parallel gripper; and S4, the mechanical arm executes the motion control instruction, and moves to the specified position, and according to the motion timing relationship in the motion control instruction, the two-finger parallel gripper is opened and clamped to complete the grabbing task. The mechanical arm grabbing method and the system for achieving the method have the beneficial effects that under the condition that the shape of the object is uncertain, a single visual sensor can be used for achieving the mechanical arm grabbing function with robustness.

Description

technical field [0001] The invention relates to the technical field of robots, in particular to a method and system for grabbing a mechanical arm facing objects with uncertain shapes. Background technique [0002] With the rise of the wave of artificial intelligence, robots are playing an increasingly important role in various industries. For robots, grasping is an essential skill for robots to enter the real world, such as sorting objects in the logistics industry and assembling parts on industrial production lines. However, there are still many uncertainties in the robot's grasping task that need further research. Therefore, how to deal with uncertainty so as to improve the success rate of crawling is a problem worthy of research. [0003] Generally, the uncertainty in the grasping process mainly includes the shape uncertainty of the object to be grasped, the uncertainty of the attitude of the object to be grasped, the uncertainty of the contact point of the manipulator,...

AI Technical Summary

Problems solved by technology

The second method is to obtain the grasping model of the robotic arm through a large amount of experimental data training. To obtain so much data, it takes a long enough time and the operation of the robotic arm to complete enough grasping times, which greatly reduces the service life of the robotic arm.

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