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Robot Control

Nattee Niparnan. Robot Control. Behavior Based Robotic. Towards Autonomous Robot. A robot that can “think” how to perform the task. Autonomous?. Able to do things by itself. Robot Control System A system that decide what / when / how to do a particular thing to achieve the given task.

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Robot Control

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  1. NatteeNiparnan Robot Control

  2. Behavior Based Robotic

  3. Towards Autonomous Robot • A robot that can “think” how to perform the task

  4. Autonomous? • Able to do things by itself. • Robot Control System • A system that decide what / when / how to do a particular thing to achieve the given task

  5. Hierarchy of Control • Reductionism Follow the white rabbit Get dress  walk to the pub  talk choose a shirt  wear a shirt Move a hand to wardrobe

  6. Robot = ??? • “ A device that connects sensing to actuation in an intelligent way” Intelligent

  7. Model-Based approach • Sense  Plan  Act

  8. Model-Based approach • Understand the world • Planning according to the state of the world • Result in rules for actions • If … then … • If … then … • . • .

  9. Remember the Shakey?

  10. Robot Control Issue • Model of the world? • Robust?

  11. Problem of model based • It seems reasonable • Does it work well in practice? • Model can hardly be realized • Model based is more appropriated with structured environment • Parallel nature? • GIGO issue

  12. Problem of model based • Example, • Self Charging • Walk to beacon • Engage charger approach maneuver • Plug-in • stop • What if we are near the charger?

  13. Problem of model based • What if we are near the charger? • Does our plan cover this case? • Coupling between requirement • Usually bug prone • Model based is sometime “computer oriented”

  14. Computer vs. Robot • All computers are equivalent (turing machine) • Any two robots are different

  15. Truth about Robot • Robots have sensors that measure the aspect of external worlds • Robots have actuators that can act on the robot and on the world • The output of a robot’s sensors always includes noise and other errors • The commands given to a mobile robot’s actuators are never executed faithfully.

  16. Sensing • For us (human)… • For them (robot)…

  17. Actuation • Electrical signal  Physical quantity • Always has some error

  18. Intelligence • Robot design + Robot’s Program + Robot’s environment = Robot’s Intelligence

  19. Mobile vs. Immobile Robots

  20. Mobile vs. Immobile Robots

  21. Example • Collecting a puck and put it into light

  22. Tasks • Show gizmo and collection tasks in Bsim • What we have as a low level command?

  23. Behavior based control • What are used in Gizmo

  24. Example of Behavior Based

  25. Behavior based robotics

  26. Behavior based robotics • Reflexive • Shortest time from sense  act • Carefully engineered the reflex to actually perform the task

  27. Principle • World = what robot sees • Plan less • Check  Act more • Be highly adaptable to change • Agility?

  28. Intro to Control

  29. Lower Level Control • Given desired output • Find input that yield such output

  30. System Input U Black Box (grey box) System Output Y

  31. Control • We hardly understand our system • The mathematical model “approximately” describe the system • There always be some error • There might be some unknown rule!

  32. Example • Do we know the speed of motor • If we apply some specific voltage? • Without actually measuring? • i.e., forward computation • We have all the theory, right?

  33. So what? • If we don’t really understand the system • How do we calculate U for given Y? • I want my motor to spin at 200rpm • What voltage should I put? • Who knows?

  34. The Solution • Control System • Open loop • Closed loop

  35. Control System • Open loop

  36. Open Loop • Just supply input • From the model • Example • Light bulb • Electric fan

  37. Open Loop • Neglect input • Hence, does not adapt itself to the world • Very simple • Easily failed • Work perfectly if we know perfect model of the system • Which is not usually the case

  38. Control System • Open loop

  39. Control System • Closed loop

  40. Feedback Control • Very important to accommodate error • We already did that all the time • Your body • Your brain • Your eco system

  41. TrichotomyMeasurement • Yes • More • Less

  42. Proportional Controller • Feedback with degree • Include error of the output • Multiply by the proportion of the error • i.e., gain of the control

  43. Closed-Loop Control Example • Position Control

  44. BSim • Gizmo task

  45. Problems • Slow to adapt • Solve by increase gain

  46. BSim again • Try to increase gain

  47. Control System Catastrophe

  48. Latency Problem • Result from the control does not actually reflect the current state • Lead to instability • Sometime to catastrophe

  49. Control System Stability

  50. PID Controller

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