The use of reinforcement learning in the task of moving objects with the robotic arm

Abstract

The article describes the task of controlling a robotic arm to transfer objects in front of it. To select actions, the reinforcement learning algorithm is used. In conclusion, there are presented the results of experiments in the Gazebo simulation environment with two different inputs: either with information about the position of the hand and the object, or with information about the position of the hand and the image with the camera.