State is what the robot collects in order to understand the world.

(not too happy about these definitions…)

• Internal state: Directly observable state of the robot. Also it's internal representation of the world - it's internal model.
• External state: What's happening in the real world. Can only be known via a robot's sensors.
• Observable state: known at all times, usually internal - eg. battery state.
• Partially observable state: Through a sensor, along with noise eg: camera image pixels
• Hidden state: What you are actually interested in, in the real world - eg: position of user's head. Can't be directly known, must be indirectly inferred from (maybe multiple) sensors. See sensor fusion.

Deliberative vs Reactive

• Capable of learning and prediction
• Finds strategic solution

but:

• Requires lots of computation - eg. brute force search for potential plan
• Needs a world model
• Slow

For example : Shakey, the first robot built with a planning AI system (running on a PDP-10 and PDP-15 computer).

• Fast
• Powerful, biological parallel

but:

• Minimal state
• No memory
• No internal representation of the world
• Unable to plan ahead
• Unable to learn

For example: BEAM robots which stands for Biology, Electronics, Aesthetics, Mechanics, and was originally invented by Mark Tilden.

• Deliberative system on top
• Reactive underneath
• Hybrid or Behavioural system

Artificial Intelligence versus classical Robotics: http://www.ee.pdx.edu/~mperkows/CLASS_479/hardware/014.Robot-Control-Architectures.ppt

http://eng.upm.edu.my/~kmbs/teaching/robotics/W6.pdf