𝗥𝗼𝗯𝗼𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: 𝗔 𝗧𝘂𝘁𝗼𝗿𝗶𝗮𝗹
Robots need to learn to perform tasks.
Traditional programming tells a robot exactly what to do. This approach fails when environments change. Robot learning changes this. It allows machines to learn from data and experience.
Key concepts in robot learning:
- Reinforcement Learning: The robot learns by trial and error to maximize rewards.
- Imitation Learning: The robot watches a human perform a task and copies the movements.
- Simulation to Reality: You train a robot in a digital world before moving it to the physical world.
This field bridges the gap between software and physical movement. It makes machines more adaptable to the real world.
Read the full guide here:
Source: https://dev.to/paperium/robot-learning-a-tutorial-230p
Optional learning community: https://t.me/GyaanSetuAi