AI for Robotics
Machine learning in robotic systems.
Perception
Computer vision for object detection. SLAM for localization. Sensor fusion.
Control
RL for motor control. Imitation learning from demonstrations. Sim-to-real transfer.
Manipulation
Grasp planning. Dexterous manipulation. Language-guided manipulation.
Key Takeaways
- RL for motor control
- Sim-to-real is challenging
- Language-guided robotics emerging