1. AIMA 25.1-25.4 Introduction to Robotics Presented by Derek Colla [additions by Simon Levy]

2. 25.1: Introduction Robot – active, artificial agent whose environment is the physical world Autonomous robots- make decisions of their own We will focus on these

3. Five properties of environments Inaccessible sensors are imperfect, and can only perceive stimuli close by Nondeterministic robot needs to deal with uncertainly, because problems arise (broken parts, batteries run low, etc.)

4. Five properties of environments Nonepisodic the effects of an action change over time, so robot must handle sequential decision problems and learn. Dynamic robot must know when it is worth deliberating, and when to act immediately

5. Five properties of environments Continuous In the real world, states and action are drawn from a continuum of physical configurations and motions. This makes it impossible to enumerate the set of possible actions.

6. 25.2: Tasks: What are robots good for? Manufacturing and materials handling traditional domains. Robots used in manufacturing are not usually autonomous. Gofer robots mobile robots (mobots) that serve as couriers and security guards in hospitals and office buildings currently becoming widely used

7. 25.2: Tasks: What are robots good for? Hazardous environments Clean-up and maintenance, rescue operations, and space and deep-sea exploration (Mars Rover) Telepresence and Virtual Reality Things such as having a glove with a remote sense of touch

8. Sojourner

9. 25.2: Tasks: What are robots good for? Augmentation of human abilities

10. 25.3: Parts: What Are Robots Made of? Links similar to the forearm or upper arm Joints similar to the elbow or shoulder

11. Effectors Any device that affects the environment, under the control of the robot Actuators converts software commands into physical motion Ex: electric motor Degrees of freedom describes how many independent ways the robot can move (up/down; left/right; forward/back)

12. Effectors Effectors used in two main ways: Locomotion Changing the position of the robot within its environment Manipulation Moving other objects in the environment

13. Locomotion Types of Legged Locomotion Statically stable A robot that can pause at any stage during its gait without tumbling over Slow and energy inefficient Dynamically stable A robot that would crash if forced to pause, but does well as long as it keeps moving Usually use a hopping motion

14. Static Stability Ocotopod, by Prof. David Livingston (VMI)

15. Dynamic Stability Hopper, by Prof. Marc Raibert MIT Leg Lab (http://www.ai.mit.edu/projects/leglab/)

16. Dynamic Stability Hopper, by Prof. Marc Raibert MIT Leg Lab (http://www.ai.mit.edu/projects/leglab/)

17. Locomotion Wheel or tread locomotion is the most practical for most environments More efficient Easier to build Easier to program Thought question: So why no wheels in nature???

18. Locomotion Important distinction between how actuators move, and what effect these motions do to the environment Car Example Turn wheel---Change direction of the car

19. Locomotion If the controllable degrees of freedom is less than the total degree of freedom, than the robot is nonholonomic The larger the gap, the harder it is to control the robot If the controllable degrees of freedom are equal to the total, then the robot is holonomic These have a high mechanical complexity

20. Manipulation Kinematics The study of the correspondence between the actuator motions in a mechanism, and the resulting motion of its various parts (same word as “cinema” : one frame at a time) Rotary motion Rotation around a fixed hub Prismatic motion Linear movement, as with a piston inside a cylinder (prism = general elongated polygon, e.g., triangular glass prism to refract light)

21. Manipulation

22. Six degrees of freedom A free body in space has six degrees of freedom (three for x-y-z position, three for orientation), so six is the minimum number of joints a robot requires in order to be able to get the last link into an arbitrary position and orientation End effector at the end of a manipulator Can be screwdriver, suction cup, etc.

23. Sensors: Tools for perception Proprioception Sense to tell a robot where its joints are Humans have this as well Encoders fitted to the joints provide very accurate data about joint angle or extension Allows robots to have a great degree of positioning accuracy, much better than humans

24. Sensors: Tools for perception Repeatability How your positioning improves given more than one try Odometry measures length of movement, can be error prone due to slippage

25. Sensors Force sensors Needed for things like scraping paint off a window Compliant motions Moving along a surface while maintaining contact with a fixed applied pressure

26. Sensors Tactile sensing robotic version of the human sense of touch Sonar Sound navigation and ranging Used mostly for fast collision avoidance Also can position obstacles Difficulties with mapping though

27. Sensors Camera data Domain constraints can help simplify things for special-purpose robots Structured light sensors Project their own light source onto objects to simplify the problem of shape determination

28. 25.4: Architectures Purpose Defines how the job of generating actions from percepts is organized Classical Architecture Hierarchy Intermediate-level actions and low-level actions incorporated to reduce errors Compiled results into macro-operators to allow the robot to learn.

29. Architectures Situated automata The principle drawback of the classical view is that explicit reasoning about the effects of low-level actions is too expensive to generate real-time behavior. A situated automaton is a machine whose inputs are provided by sensors connected to the environment, and whose outputs are connected to effectors. The s.a. has only a limited (finite) number of possible states.

30. Situated Automata Very efficient implementation of reflex agents with state. Implements specific laws, such as the laws of physics given to the compiler, and uses those to make propositions

31. Behavior-based Robotics Based on the idea that the agent design can be decomposed, not into functional components such as perception, learning, and planning, but into behaviors such as obstacle avoidance, wall-following, and explorations. Contrasts with planning approach : robot thinks for a long time about how to accomplish a goal, then acts.

32. Behavior-based Robotics Genghis, by Prof. Rodney Brooks MIT AI Lab / iRobot Corp (Roomba)

33. Behavior-based Robotics Genghis, by Prof. Rodney Brooks MIT AI Lab / iRobot Corp (Roomba)