Chapter 7: Artificial Intelligence in Robotics
6 sections
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Sections
Navigate through the learning materials and practice exercises.
What we have learnt
- AI enhances robots with learning, adaptability, and autonomy.
- Machine learning allows robots to improve from data without explicit programming.
- Reinforcement learning helps in optimizing robot behavior through environmental interactions.
- Cognitive robotics aims to integrate human-like reasoning into robots.
- Robots often operate under uncertainty requiring advanced planning frameworks such as POMDP.
Key Concepts
- -- Machine Learning (ML)
- A technique that empowers robots to learn from data and improve actions without explicit programming.
- -- Reinforcement Learning (RL)
- An area of machine learning where agents learn optimal behaviors through rewards based on interactions with their environment.
- -- POMDP (Partially Observable Markov Decision Process)
- A framework used to plan actions under uncertainty where a robot maintains a belief state—probability distributions over possible states.
- -- Cognitive Robotics
- A field focused on embedding human-like reasoning and learning into robotic systems.
- -- BehaviorBased System
- A robotic architecture where behaviors are layered hierarchically and operate concurrently, enhancing reactivity.
Additional Learning Materials
Supplementary resources to enhance your learning experience.