Deep Reinforcement Learning for Robotics Vision: Exploring deep reinforcement learning techniques for robotics vision tasks, including object manipulation and navigation
Keywords:
Deep Reinforcement Learning, Robotics VisionAbstract
Deep reinforcement learning (DRL) has emerged as a powerful approach for robotics vision, enabling robots to learn complex tasks such as object manipulation and navigation. This paper explores the application of DRL techniques to robotics vision, focusing on how deep neural networks can be trained to perceive and interact with the environment. We discuss key challenges in this domain, such as sample efficiency and generalization, and review recent advances that have addressed these challenges. Additionally, we present case studies of successful applications of DRL in robotics vision, highlighting the potential of this approach to revolutionize robotic systems' capabilities in real-world scenarios.
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