Robotic Arm Representation Using Image-Based Feedback for Deep Reinforcement Learning

2019 IEEE Jordan International Joint Conference on Electrical Engineering and Information Technology (JEEIT)（2019）

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Abstract

This paper presents a technique that uses feedback images for implementing a robotic task using Deep Reinforcement Learning (DRL). The agent (controller) type is Actor-Critic that uses Temporal-Difference (TD) to gain knowledge about the environment (plant). The representation of the robot is implemented in the V-Rep simulator.

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Key words

Deep Reinforcement Learning,Arm robot,manipulator,image processing,Actor-Critic,V-Rep

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