2. Introduction to Robotics In the name of Allah

3. Introduction to Robotics o Leila Sharif o l_sharif@sharif.edul_sharif@sharif.edu http://ce.sharif.edu/courses/84-85/1/ce516/ o Lecture #4: Effectors and Actuators

4. Introduction to Robotics Lecture Outline  A brief history of robotics  Feedback control  Cybernetics  Artificial Intelligence (AI)  Early robotics  Robotics today  Why is robotics hard?  Degrees of Freedom (DOF)  holonomicity, redundancy  Legged locomotion  stability (static and dynamic)  polygon of support  Wheeled locomotion  Trajectory/motion planning

5. Introduction to Robotics Feedback Control  Feedback: continuous monitoring of the sensors and reacting to their changes.  Feedback control = self-regulation  Two kinds of feedback:  Positive  Negative  The basis of control theory

6. Introduction to Robotics - and + Feedback  Negative feedback  acts to regulate the state/output of the system  e.g., if too high, turn down, if too low, turn up  thermostats, bodies, robots...  Positive feedback  acts to amplify the state/output of the system  e.g., the more there is, the more is added  stock market,...

7. Introduction to Robotics Cybernetics  Pioneered by Norbert Wiener (1940s)  (From Greek “steersman” of steam engine)  Marriage of control theory (feedback control), information science and biology  Seeks principles common to animals and machines, especially for control and communication  Coupling an organism and its environment (situatedness)

8. Introduction to Robotics Early Artificial Intelligence  “Born” in 1955 at Dartmouth  “Intelligent machine” would use internal models to search for solutions and then try them out (M. Minsky) => deliberative model!  Planning became the tradition  Explicit symbolic representations  Hierarchical system organization  Sequential execution

9. Introduction to Robotics Artificial Intelligence (AI)  Early AI had a strong impact on early robotics  Focused on knowledge, internal models, and reasoning/planning  Basis of deliberative control in early robots

10. Introduction to Robotics Early Robots: SHAKEY  At Stanford Research Institute (late 1960s)  Vision and contact sensors  STRIPS planner  Visual navigation in a special world  Deliberative

11. Introduction to Robotics Early Robots: HILARE  LAAS in Toulouse, France (late 1970s)  Video, ultrasound, laser range-finder  Still in use!  Multi-level spatial representations  Deliberative -> Hybrid Control

12. Introduction to Robotics Early Robots: CART/Rover  Hans Moravec  Stanford Cart (1977) followed by CMU rover (1983)  Sonar and vision  Deliberative control

13. Introduction to Robotics Robotics Today  Assembly and manufacturing (most numbers of robots, least autonomous)  Materials handling  Gophers (hospitals, security guards)  Hazardous environments  Remote environments  Surgery (brain, hips)  Tele-presence and virtual reality  Entertainment

14. Introduction to Robotics Why is Robotics hard?

15. Introduction to Robotics Why is Robotics hard?  Sensors are limited and crude  Effectors are limited and crude  State (internal and external, but mostly external) is partially- observable  Environment is dynamic (changing over time)  Environment is full of potentially- useful (and useless) information

16. Introduction to Robotics Key Issues  Grounding in reality: not just planning in an abstract world  Situatedness (ecological dynamics): tight connection with the environment  Embodiment: having a body  Emergent behavior: interaction with the environment  Scalability: increasing task and environment complexity

17. Introduction to Robotics Definition of Effector  An effector is any device that has an effect on the environment.  A robot’s effectors are used to purposefully effect the environment.  E.g., legs, wheels, arms, fingers...  The role of the controller is to get the effectors to produce the desired effect on the environment, based on the robot’s task.

18. Introduction to Robotics Definition of Actuator  An actuator is the actual mechanism that enables the effector to execute an action.  E.g, electric motors, hydraulic or pneumatic cylinders, pumps…  Actuators and effectors are not the same thing.  Incorrectly thought of the same; “whatever makes the robot act”

19. Introduction to Robotics Degrees of Freedom  Most simple actuators control a single degree of freedom (DOF)  Think of DOFs as ways in which a motion can be made (e.g., up-down, left-right, in-out)  E.g., a motor shaft controls one rotational DOF; a sliding part on a plotter controls one translational DOF.

20. Introduction to Robotics Counting DOF  A free body in space has 6 DOF  3 are translational (x, y, z)  3 are rotational (roll, pitch, and yaw)  Every robot has a specific number of DOF  If there is an actuator for every DOF, then all of the DOF are controllable  Usually not all DOF are controllable  This makes robot control harder

21. Introduction to Robotics Example: DOF of a Car  A car has 3 DOF: position (x,y) and orientation (theta)  Only 2 DOF are controllable  driving: through the gas pedal and the forward-reverse gear  steering: through the steering wheel  Since there are more DOF than are controllable, there are motions that cannot be done, like moving sideways (that’s why parallel parking is hard)

22. Introduction to Robotics Actuators and DOFs  We need to make a distinction between what an actuator does (e.g., pushing the gas pedal) and what the robot does as a result (moving forward)  A car can get to any 2D position but it may have to follow a very complicated trajectory  Parallel parking requires a discontinuous trajectory w.r.t. velocity, i.e., the car has to stop and go

23. Introduction to Robotics Holonomicity  When the number of controllable DOF is equal to the total number of DOF on a robot, it is holonomic.  If the number of controllable DOF is smaller than total DOF, the robot is non-holonomic.  If the number of controllable DOF is larger than the total DOF, the robot is redundant.

24. Introduction to Robotics Redundancy  A human arm has 7 DOF (3 in the shoulder, 1 in the elbow, 3 in the wrist), all of which can be controlled.  A free object in 3D space (e.g., the hand, the finger tip) can have at most 6 DOF!  => There are redundant ways of putting the hand at a particular position in 3D space.  This is the core of why manipulations is very hard!

25. Introduction to Robotics Uses of Effectors  Two basic ways of using effectors:  to move the robot around =>locomotion  to move other object around =>manipulation  These divide robotics into two mostly separate categories:  mobile robotics  manipulator robotics

26. Introduction to Robotics Locomotion  Many different kinds of effectors and actuators are used for locomotion:  legs (walking, crawling, climbing, jumping, hopping…)  wheels (rolling)  arms (swinging, crawling, climbing…)  flippers (swimming)  Most animals use legs, but most mobile robots use wheels, why?

27. Introduction to Robotics Stability  Stability is a necessary property of mobile robots  Stability can be  static (standing w/o falling over)  dynamic (moving w/o falling over)  Static stability is achieved through the mechanical design of the robot  Dynamic stability is achieved through control

28. Introduction to Robotics More on Stability  E.g., people are not statically stable, but are dynamically stable! It takes active control to balance. This is mostly unconscious.  Static stability becomes easier with more legs.  To remain stable, a robot’s center of gravity (COG) must fall under its polygon of support (the area of the projection of its points of contact onto the surface)

29. Introduction to Robotics Polygon of Support  In two-legged robots/creatures, the polygon of support is very small, much smaller than the robot itself, so static stability is not possible (unless the feet are huge!)  As more legs are added, and the feet spread out, the polygon gets larger  Three-legged creatures can use a tripod stance to be statically stable

30. Introduction to Robotics Statically Stable Walking  Three legs are enough to balance, but what about walking?  If a robot can stay continuously balanced while walking, it employs statically stable walking  Impossible with 3 legs; as soon as one is off the ground, only 2 are left, which is unstable  How many legs are needed for statically stable walking?

31. Introduction to Robotics Good Numbers of Legs  Since it takes 3 legs to be statically stable, it takes at least 4 to walk statically stable  Various such robots have been built  6 legs is the most popular number as they allow for a very stable walking gait, the tripod gait  3 legs are kept on the ground, while the other 3 are moved forward

32. Introduction to Robotics The Tripod Gait

33. Introduction to Robotics The Tripod Gait  If the same three legs move at a time, this is called the alternating tripod gait  if the legs vary, it is called the ripple gait  All times, a triangle of support stays on the ground, and the COG is in it  This is very stable and thus used in most legged robots

34. Introduction to Robotics Tripod Gait in Biology  Cockroaches and many other 6-legged insects use the alternating tripod gait  Note: numerous insects have 6 legs  Insects with more than 6 legs (e.g., centipedes and millipedes), use the ripple gate  Insects can also run very fast by letting go of the ground completely every once in a while, and going airborne…

35. Introduction to Robotics Dynamic Stability  Statically stable walking is very energy inefficient  As an alternative, dynamic stability enables a robot to stay up while moving  This requires active control (i.e., the inverse pendulum problem)  Dynamic stability can allow for greater speed, but requires harder control

36. Introduction to Robotics Wheels v. Legs  Because balance is such a hard control problem, most mobile robots have wheels, not legs, and are statically stable  Wheels are more efficient than legs, and easier to control  There are wheels in nature, but legs are by far more prevalent, though in terms of population sizes, more than 2 legs (i.e., insects abound)

37. Introduction to Robotics Varieties of Wheels  Wheels are the locomotion effector of choice in most mobile robots  Wheels can be as innovative as legs  size and shape variations  tire shapes and patterns  tracks  wheels within wheels and cylinders  different directions of rotation ...

38. Introduction to Robotics Wheels and Holonomicity  Having wheels does not imply holonomicity  2 or 4-wheeled robots are not usually holonomic  A popular and efficient design involves 2 differentially-steerable wheels and a passive caster

39. Introduction to Robotics Differential Steering  Differential steering means that the two (or more) wheels can be steered separately (individually)  If one wheel can turn in one direction and the other in the opposite direction, the robot can spin in place  This is very helpful for following arbitrary trajectories  Tracks are often used (e.g., tanks)

40. Introduction to Robotics Trajectories  In locomotion we can be concerned with:  getting to a particular location  following a particular trajectory (path)  Following an arbitrary given trajectory is harder, and it is impossible for some robots (depending on their DOF)  For others, it is possible, but with discontinuous velocity (stop, turn, and then go again)

41. Introduction to Robotics Trajectory Planning  A large area of traditional robotics is concerned with following arbitrary trajectories  Why? Because planning can be used to compute optimal (and thus arbitrary) trajectories for a robot to follow to get to a particular goal location  Practical robots may not be so concerned with specific trajectories as with just getting to the goal location

42. Introduction to Robotics More Trajectory Planning  Trajectory planning is a computationally complex process  All possible trajectories must be found (by using search) and evaluated  Since robots are not points, their geometry (i.e., turning radius) and steering mechanism (holonomicity properties) must be taken into account  This is also called motion planning