Robotic-fall05-4 - Computer Engineering

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Transcript Robotic-fall05-4 - Computer Engineering

In the name of Allah
Introduction to Robotics
Introduction to Robotics
 Leila Sharif
 [email protected]
http://ce.sharif.edu/courses/84-85/1/ce516/
 Lecture #4: Effectors and Actuators
Introduction to Robotics
Lecture Outline
 A brief history of robotics
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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
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
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, ...
Introduction to Robotics
Cybernetics
 Pioneered by Norbert Wiener (1940s)
 (From Greek “steersman” of steam engine)
 Marriage of control theory (feedback
information science and
biology
 Seeks principles common to animals
and machines, especially for control
and communication
 Coupling an organism and its
environment (situatedness)
Introduction to Robotics
control),
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
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
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
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
Introduction to Robotics
Early Robots: CART/Rover
 Hans Moravec
 Stanford Cart
(1977) followed by
CMU rover (1983)
 Sonar and vision
 Deliberative control
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
Introduction to Robotics
Why is Robotics hard?
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 partiallyobservable
 Environment is dynamic (changing
over time)
 Environment is full of potentiallyuseful (and useless) information
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
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.
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”
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.
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
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)
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
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.
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!
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
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?
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
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)
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
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?
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
Introduction to Robotics
The Tripod Gait
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
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…
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
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)
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
 ...
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
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)

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)
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
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
Introduction to Robotics