Definition
Robot learning involves training robotic agents to perform tasks autonomously by leveraging machine learning techniques. Unlike pre-programmed behaviors, these systems adapt to dynamic environments using methods like reinforcement learning, imitation learning, and evolutionary algorithms. The goal is to develop robust control policies that allow robots to generalize from limited data, handle uncertainties, and continuously refine their motor skills and decision-making processes over time.
Summary
A subfield of robotics focused on enabling robots to acquire skills and improve performance through experience and interaction with their environment.
Key Concepts
- Reinforcement learning
- Imitation learning
- Sim-to-real transfer
- Motor control
Use Cases
- Autonomous warehouse picking
- Humanoid gait adaptation
- Robotic surgery assistance