1. Short History of Robotics

2. Pre-History of Real-World Robots:
One of the first robots was the clepsydra or water clock, which was made in 250 B.C.
It was created by Ctesibius of Alexandria, a Greek physicist and inventor.
Hero from Alexandria built robot theater

3. Jacques de Vaucanson (1709-1782)
Master toy maker who won the heart of Europe.
Flair for inventing the mechanical revealed itself early in life.
He was impressed by the uniform motion of the pendulum of the clock in his parents hall.
Soon he was making his own clock movements.

4. James Watt

5. Mechanical horse

6. Pre-History of Real-World Robots:
The earliest remote control vehicles were built by Nikola Tesla in the 1890's.
Tesla is best known as the inventor of AC power, induction motors, Tesla coils, and other electrical devices.

7. Robots of the media

8. History of Robotics? Popular culture influenced by these ideas RUR
Metropolis(1927)
Forbidden planet(1956)
2001 A Space Odyssey(1968)
Logans Run(1976)
Aliens(1986)

9. Robot Continuum
Robot continuum
...
1921

10. Robot Continuum
Karl Capek
...
1921
2020

11. Robot Continuum
Robot continuum
Karl Capek
Dalek
...
1921
2020
2150

12. Robot Continuum ... Robot continuum 1921 2020 2150 2421 Karl Capek
Dalek
...
1921
2020
2150
2421

13. Robot Continuum ... Robot continuum Let us step down fantasies…..
“Tortoise”
...
1951

14. History of Real-World Robots:
Other early robots (1940's - 50's) were Grey Walter’s “Elsie the Tortoise” ("Machina speculatrix") and the Johns Hopkins "beast."
History of Real-World Robots:

15. Grey Walter's tortoise, restored recently by Owen Holland and fully operational
What are robots made of?
Sensors: Light Sensors
This robot was developed by Grey Walter, a prominent neurophysist, in the 1940s-50s. I had two neurons but could do a lot with just those two. It could search out a light source to recharge its battery cells and wiggle if it got stuck. Grey Walter also trained it by blowing a whistle and immediately kicking. After the fifth or sixth kick, the robot would move back from the imagined obstacle it was about to it.
Grey Walter’s Tortoise

16. Isaac Asimov and Joe Engleberger
Two fathers of robotics
Engleberger built first robotic arms

17. History of Real-World Robots:
The first modern industrial robots were probably the “UNIMATES”, created by George Devol and Joe Engelberger in the 's and 60's.
Engleberger started the first robotics company, called "Unimation", and has been called the "father of robotics."
Unimates, late 50’s to early 60’s
Automotive Industry
Recent Recovery
Worth over $500 million
99% are industrial

18. The Advent of Industrial Robots - Robot Arms
There is a lot of motivation to use robots to perform task which would otherwise be performed by humans:
Safety
Efficiency
Reliability
Worker Redeployment
Cheaper

19. What are they?
Most of the industrial robots used in factories throughout the world exhibit few of the characteristics that the average person would associate with the term "robot"
Many are simple "pick and place" machines
Lets have a working definition for an industrial robot
These machines are programmable, are automatic and can perform a wide variety of tasks

20. Robot Manipulators

21. Pick and Place Machines (robots?)
Simplest kind of industrial robot
Still some on production lines but are being phased out
Perform simple pickup and drop functions
Cannot sense environment
The limits of motion of each joint of the machine are fixed by electric or pneumatic impulse originating at a plug-board control panel

22. Servo Robots
A more sophisticated level of control can be achieved by adding servomechanisms that can command the position of each joint.
The measured positions are compared with commanded positions, and any differences are corrected by signals sent to the appropriate joint actuators.
This can be quite complicated

23. What are robots made of? Effectors: Manipulation Degrees of Freedom
Degrees of freedom descrribes the number of ways that a robot can move. In order to reach any possible point in space within its work envelope, a robot needs a total of 6 degrees of freedom. The human arm has 6 degrees of freedom, in total a human has about 111.

24. Degrees of Freedom
For the robot arms to become more flexible, more "degrees of freedom" or planes of free movement had to be added.
Many industrial arms have 6 or more planes of motion

25. Teach and Play-back Robots
Once the math is solved it is a relatively simple matter to teach a robot how to pick something up and what to do with it.
Teaching involves moving the arm through the motions it is expected to perform
During Recall mode the arm repeats, verbatim, what it has been taught

26. Teach and Play-back Robots

27. An Arm's Simple World
Life is simpler for a robot arm which can always expect objects to be oriented in the same way.
It only has to worry about its own coordinate system.
The math gets complex but is manageable

28. The U.S. military contracted the "walking truck" to be built by the General Electric Company for the U.S. Army in 1969.
Walking robots

29. History of Real-World Robots:
The walking truck was the first legged vehicle with a computer-brain, developed by Ralph Moser at General Electric Corp. in the 1960s.
It was a large (3,000 pounds) four legged robot that could walk up to four miles a hour.

30. The Army and the Artificial Elephant
General Electric Walking Truck.
A human controlled the stepping of this robot by pushing pedals with his feet.
The complicated coordination of movements within a leg and between different legs during stepping was controlled by a computer

31. The Army and the Artificial Elephant
Project failed because of the "unanticipated computational difficulty" of simultaneously controlling all of the degrees of freedom in the four legs.
This failure dramatically demonstrated the sophistication that control systems must have to produce successful walking behavior in legged mechanisms.

32. Marvin Minsky MIT Pioneer of AI and Robotics
Robotics and AI are very new research areas, most pioneers are alive and well.

33. Over Confidence
Soon people had faith in their own ability to solve what turned out to be extremely complex control problems

34. A Robot's More Complex World
It gets more complex when you expect an arm to pick up objects which can be in any orientation.
There are several problems
How do you pick it up?
How do you recognize it is there?
How do you know you are holding it firmly?
How do you have to change your grip to hold it the way you need to?
This is still a subject of much research

35. Expanding Horizons
Undaunted by previous failures, robotocists continued research in the field
People thought a good strategy would be:
to start from the state-of-the-art as practiced in industrial robotics
and gradually expand the sensory and control capabilities
until the more difficult tasks became tractable.
This was the strategy adopted by the robotics group at S.R.I

36. History of Real-World Robots:
“Shakey" was a small unstable box on wheels that used memory and logical reasoning to solve problems and navigate in its environment.
It was developed by the Stanford Research Institute (SRI) in Palo Alto, California in the s.

37. Shakey of Nilsson ... ... Shakey
Nils Stanford Research Inst.
first “general-purpose” mobile platform
...
...
1968

38. Shakey the robot.
Shakey was the first mobile robot that could think independently and interact with its surroundings
Conceived as a demonstration project for the Advanced Research Projects Agency (ARPA) artificial Intelligence program

39. Shakey (cont)
Shakey could be given a task such as finding a box of a given size, shape, and color and told to move it to a designated position.
Shakey was able to search for the box in various rooms, cope with obstacles, and plan a suitable course of action.
It was controlled by an off-board PDP-10 computer through a radio link.
It carried :
a TV camera,
an optical range finder,
and touch sensors
so that it could know when it bumped into something.

40. Shakey (cont) Shakey (cont)
While Shakey was a success in some respects it was a great failure as far as autonomy was concerned...
It was controlled by an off-board computer
It could only detect the baseboards of the special rooms it worked in
It could not deal with an unconstrained environment
It was really slow!

41. Shakey (cont) ... ... Shakey Nils Nilsson @ Stanford Research Inst.
first “general-purpose” mobile platform
Living Room (L)
Kitchen (K) sp tv sh
tvg
Bedroom (B)
...
...
1968

42. Shakey (cont) Shakey Start START Go(x,y) Preconditions: At(sh,x)
Postconditions: At(sh,y)
Push(obj,x,y)
Preconditions: At(sh,x)  At(obj,x)
Postconditions: At(sh,y)  At(obj,y)
ACTIONS
At(sh,L)  At(sp,K)  At(tvg,B)  At(tv,L)
Go(L,B)
Push(tv,L,B)
Go(L,K)
Push(tv,L,K)
At(sh,K)  At(sp,K)  At(tvg,B)  At(tv,K)
At(sh,L)  At(sp,L)  At(tvg,L)  At(tv,L)
GOAL

43. Stanford Cart ... ... Stanford Cart Hans Moravec @ SAIL SENSING ACTING
“functional” task decomposition
SENSING
ACTING
perception
world modeling
planning
task execution
motor control
...
...
1976

44. AI - Historical Perspective
Artificial Intelligence began with very ambitious goals in the 1950s & 60s
Most initial work on AI focused on severely abstracted “toy problems”
Recent work (mid-80s to present) has been very successful in finding applications that are firmly grounded in the real world
Intelligent assistants
Computer vision for navigation, graphics
Robotics systems for manufacturing
Speech analysis & generation
Basic observations:
Artificial Intelligence has specialized into many inter-related but distinct disciplines
Tasks performed effortlessly by humans & animals often are the hardest to emulate

45. History of AI McCulloch and Pitts (1943) Minsky (1951)
1947~1959
cybernetics
Dartmouth
1960~1964
LISP(1960)
GPS(1963)
McCulloch and Pitts (1943)
Neural networks that learn
Minsky (1951)
Built a neural net computer
Darmouth conference (1956):
McCarthy, Minsky, Newell, Simon met,
Logic theorist (LT)- proves a theorem in Principia Mathematica-Russel.
The name “Artficial Intelligence” was coined.
GPS- Newell and Simon
Geometry theorem prover - Gelernter (1959)
Samuel Checkers that learns (1952)
McCarthy - Lisp (1958), Advice Taker, Robinson’s resolution
Microworlds: Integration, block-worlds.
1962- the perceptron convergence (Rosenblatt)

46. History of AI, continued
a dose of reality
Problems with computation
Knowledge-based systems
Weak vs. strong methods
Prolog(1973)
Expert systems:
Dendral : Inferring molecular structures
Mycin: diagnosing blood infections
Prospector: recomending exploratory drilling (Duda).
Roger Shank: no syntax only semantics
: AI becomes am industry
R1: McDermott, 1982, order configurations of computer systems
1981: Fifth generation
1986-present: return to neural networks
Recent event:
Hidden Markov models, planning, belief network
EasyFinder
Excite Live
FarCast
(Electronic Commerce)
Mysimon
Amazon
CDNow
eWatch
Careersite
Intelligent Miner

47. Key Schools of Thought in AI and Robotics now
1. Symbolic AI
The physical symbol hypothesis (Newell & Simon, 1976)
A physical symbol system has the necessary & sufficient means for general intelligent action
2. Sub-symbolic AI
Connectionist/neural net approaches
Rely on signals, not symbols Intelligence emerges from connections between entities in an evolving dynamical system
The physical grounding hypothesis (Brooks, 1990)
Behavior modules of an agent interact with the environment to produce complex behavior without using centralized symbolic models

48. Rodney A. Brooks Born in Adelaide, Australia in 1954
Received Ph.D in computer science from Stanford University
Member of the M.I.T Artificial Intelligence Lab where he leads the mobile robot group.
Well funded to do research in autonomous vehicles. ($$$$)

50. The early years
Brooks was painfully aware of the failure of robotics to live up to its potential.
Autonomous vehicles were not that autonomous and weren't even very good vehicles.
He identified various aspects of mobile robotics which he considered to be important and obvious

51. Brook's Robot Requirements
He identified a number of requirements of a control system for an intelligent autonomous mobile robot.
Multiple Goals:
Some conflict, context dependent
Multiple Sensors:
All have errors, inconsistencies and contradiction.
Robustness:
The robot must by fault-tolerant.
Extensible:
You have to be able to build on whatever you built

52. Brook’s Dogma Brooks also introduced, what he called,
"9 dogmatic principles",
1) Complex (and useful) behavior need not necessarily be a product of an extremely complex control system.
2) Things should be simple: Interfaces to subsystems etc.
3) Build cheap robots that work in human environments
4) The world is three-dimensional therefore a robot must model the world in 3 dimensions.

53. Brook’s Dogma Dogma (cont)
5) Absolute coordinate systems for a robot are the source of large cumulative errors.
6) The worlds where mobile robots will do useful work are not constructed of exact simple polyhedra.
7) Visual data is useful for high level tasks. Sonar may only be good for low level tasks where rich environmental descriptions are unnecessary.
8) The robot must be able to perform when one or more of its sensors fails or starts giving erroneous readings.

54. Brook’s Dogma 9) "We are interested in building "artificial beings"
--robots that survive for days, weeks and months,
without human assistance,
in a dynamic complex environment.
Such robots must be self-sustaining

55. Subsumption
Brooks and his group eventually came up with a computational architecture.
Model arrived at by continually refining attempts to program a robot to reactively avoid collisions in a people-populated environment.
Not intended as a realistic model of how neurological systems work.
The model is called "subsumption architecture”.
Its purpose is to program
intelligent,
situated,
embodied agents.

56. Subsumption Priciples
1) Computation is organized as an asynchronous network of active computational elements:
they are augmented finite state machines,
with a fixed topology of unidirectional connections.
2) Messages sent over connections have no implicit semantics:
they are small numbers (typically 8 or 16 bits, but on some robots just 1 bit),
their meanings are dependent on the dynamics designed into both the sender and receiver
3) Sensors and actuators are connected to this network,
usually through asynchronous two-sided buffers.

57. Allen First Subsumptive Robot
Almost entirely reactive, using sonar readings to keep away from people and other moving obstacles, while not colliding with static obstacles.
Also had a non-reactive higher level which attempted to head towards a goal.
Used same type of architecture for both types of behaviors.

58. Herbert Used a laser scanner to find soda can-like objects visually,
infrared proximity sensors to navigate by following walls and going through doors.
A magnetic compass was used to maintain a global sense of orientation.
A host of sensors on an arm were used to reliably pick up a soda can.
Herbert's task was to wander around looking for soda cans, pick one up and bring it back to where Herbert had started from.

59. Where we’re at. Inch square robots. Food scavengers. Play Tag.
Find shade.

60. Squirt Smallest robot they built
Weighs 50 grams and is about 5/4 cubic inches in volume.

61. Squirt
Squirt (cont)
Incorporates an 8-bit computer, an on-board power supply, three sensors and a propulsion system.
Normal mode of operation is to act as a "bug", hiding in dark corners and venturing out in the direction of noises, only after the noises are long gone.
The entire compiled control system for Squirt fits in 1300 bytes of code on an on-board computer.

62. Genghis
Genghis is a 1Kg six legged robot which walks under subsumption control and has an extremely distributed control system
It can walk over rough terraine using 12 motors, 12 force sensors, 6 pyroelectric sensors, one inclinometer and 2 whiskers.
They built a follow-up, Attila--Stronger climber, and able to scramble at around 3 KPH.

63. Genghis (cont)
Genghis

64. From Genghis to Artificial Insects
Rodney MIT
planning and reasoning
“behavioral” task decomposition
identify objects
build maps
ACTING
SENSING
explore
wander
avoid objects
...
...
1985

65. Cartland

66. Where do we go from here?
There are many many problems that subsumption does not address, including adaptation through learning
There is still much work to be done and it doesn't have to cost that much money.
Try building one of these yourself.

67. 1.In this class you will learn programming language Lisp - especially suited for robotics. You should already know Basic of C. Think how would you program robots with behaviors described above.
2. If you feel your knowledge of programming is insufficient, start learning LISP now.
Problems
3. Many of above ideas were programmed by us in Basic. The Visual Basic environment from Microsoft allows for interfacing, voice recognition and synthesis and robot vision. If you are interested in these areas, try to review Visual Basic now. It is located on PCs in the lab.

68. Sources A. Ferworn Dodd, Harvey Mudd College Internet Padhraic Smyth
Kiriakos Kutulakos, University of Rochester
Rojas FUB MI
Behnke
A. Ferworn
Dodd, Harvey Mudd College
Internet
Brian Glassman, Mechanical Engineering at Florida Institute of Technology
John Gallagher, SUNY Institute of Technology