Chapter 26: Advances in Robotics: Reinforcement Learning for Robots Control
Abstract: Reinforcement learning (RL) is revolutionizing robotics by enabling robots to learn complex behaviors through trial and error, enhancing their control, path planning, and manipulation skills in various environments . Here's a more detailed explanation of how reinforcement learning is advancing robot control: What is Reinforcement Learning? RL is a machine learning technique where an agent (in this case, a robot) learns to make decisions in an environment to maximize a cumulative reward. How it Works: Instead of explicitly programming robot actions, RL allows robots to learn optimal behaviors by interacting with their environment and receiving feedback in the form of rewards or penalties. Benefits for Robotics: Complex Task Learning: RL enables robots to learn tasks that are difficult to program directly, such as complex manipulation, navigation, and locomotion. Adaptability: Robots can adapt to changing environments and...