1. All Teams Overview: Team:Topics 1 Overview Chapter 1: From Teleoperation to Autonomy Chapter 2: The Hierarchical Paradigm 2 Chapter 3: Biological Foundations of the Reactive Paradigm Chapter 4: The Reactive Paradigm Chapter 5: Designing a Reactive Implementation 3 Chapter 7: The Hybrid Deliberative/Reactive Paradigm

2. Team 1 Overview Name: Presents section of Book: Jorge Franco Introduction and Overview Willmert Pereyra What is a robot and brief history 1.1 – 1.4.1 George Ragousis Robot Control and Operation 1.4.2 – 1.7 Sylvester Delano GPS Strips 2.1 – 2.2.3 Alexander Torres NHC NIST RCS 2.2.4 – 2.7

3. Introduction and Overview Jorge Franco

4. Overview What is AI robotics –3 major paradigms Ways in which intelligence is organized Architectures for paradigms –Coherent –Reusable Single/Team of robots Implementations

5. What are Robots?

6. Shift from human-like servants made from biological parts to human-like servants made up of mechanical parts due to science fiction –Classics: Metropolis (1926), The Day the Earth Stood Still (1951), and Forbidden Planet (1956) Shift from human-like mechanical creatures to whatever shape gets the job done is due to reality Definition used in book: an intelligent robot is a mechanical creature which can function autonomously. What are Robots? (cont’d)

7. What are Robotic Paradigms? A paradigm is a philosophy or set of assumptions and/or rules/techniques which characterize an approach to a class of problems Why know paradigms? –Key to successfully program a robot for an application –Interesting from historical perspective Issues that spawned one the shift from one paradigm to another 3 kinds –Hierarchical –Reactive –Hybrid deliberative/reactive Described in two ways –Relationship between 3 accepted primitives Sense, Act, Plan –Way that sensory data is processed and distributed through the system

8. Robot Paradigm Primitives (fig1.2 from book) Robot Primitives InputOutput Sense Sensor dataSensed information Plan Information (Sensed and/or cognitive) Directives Act Sensed information/ directives Actuator commands

9. Sensing Organization in Robot Paradigms Way Sensory data: –Processed –Distributed Local processing –Sensor information restricted to specific/dedicated way for each robot function Global world model processing –All SI first processed into a global world model –Subsets of model distributed to other functions as needed

10. Overview of the 3 Paradigms fig.1.3 a.) Hierarchical, b.) Reactive, and c.) Hybrid deliberative/reactive a. b. c.

11. Hierarchical Paradigm 1967 – 1990 Top down fashion – Heavy on planning Introspective view –However as Cognitive Psych. now know: Not always good assessment of thought process. Default schemas or behaviors Global world model –Hard and brittle Frame problem and closed world assumption

12. Another View of the Hierarchical Paradigm (fig.1.4 from book) Robot Primitives InputOutput Sense Sensor dataSensed information Plan Sensed and/or cognitive information Directives Act Sensed information/ directives Actuator commands

13. The Reactive Paradigm (fig.1.5 from book) Robot Primitives InputOutput Sense Sensor dataSensed information Plan Sensed and/or cognitive information Directives Act Sensed information/ directives Actuator commands

14. The Hybrid Deliberative/Reactive Paradigm (fig.1.6 from book) Robot Primitives InputOutput Plan Information (Sensed and/or cognitive) Directives Sense-Act (behaviors) Sensor dataActuator commands

15. Representative Architectures Templates for an implementation Examples of what each paradigm really means According to Mataric: an architecture is a principled way of organizing a control system, with constraints on the way the control problem can be solved Common components in robot architecture and rules of thumb for placing them together –IC car –paradigm –Each car manufacturer has its own architecture –The car manufacturers may have slight modification on their architecture for sedans, convertibles, SUV’s,etc.

16. Set Criteria for the Evaluation of an Architecture Modularity Niche Targetability Portability Robustness

17. Layout of the Section Divided into 8 chapters –1. define Robotics –2. describes Hierarchical Paradigm and 2 architectures –3. sets the stage for understanding the Reactive Paradigm and the motivation that spawned it. –4. Describes the Reactive Paradigm and popular architecture –5. Provides guidelines and case studies on designing robot behaviors –6. Discusses simple sonar and computer vision processing techniques –7. Describes the Hybrid Deliberative-Reactive Paradigm –8. Discusses how the principles of the 3 paradigms have been transferred to team of robots

18. Sections 1.1 –1.4.1 Willmert Pereyra

19. Uses of Robots Dirty jobs. Dull jobs. Dangerous jobs.

20. Robotics Timeline Planetary rovers vision manufacturing AI robotics Telesystems Industrial manipulators Telemanipulators 19601970198019902000

21. Old Movies About Robots Modern Times (Charlie Chaplin), 1936. Metropolis, 1927. Silent Running, 1972. The Phantom Menace, 1999.

22. Modern Times 1937

23. Metropolis 1927

24. Silent Running 1972

25. The Phantom Menace 1999

26. Approaches to Robotics Artificial Intelligence (AI). Engineering.

27. AI vs. Engineering AI: –Uses paradigms. –All actions are human-like. Engineering: –Does not use paradigms. –Actions performed are mechanical.

28. Engineering Control Types Ballistic control: –The position, trajectory and velocity profiles are computed once. Feedback control: –The error between the goal and current position is noted by a sensor(s): a new trajectory and profile is computed and executed. Then modified in the next update.

29. AI Robotics Terms Intelligent Robot: –A mechanical creature which can function autonomously. Paradigm: –A philosophy or set of assumptions and/or techniques which characterize an approach to a class of problems.

30. AI Robotics Terms Luddites: –People who object to robots, or technology in general. Artificial Intelligence (AI): –(1) Science of making machines act intelligently. (2) The study of ideas that enable computers to be intelligent. (3) An attempt to make computers do things that at present people are better at.

31. AI Robotics Terms Teach pendant: –A device that enables the programmer to guide the robot through the desired set of motions. Automatic Guided Vehicle (AGV): –A vehicle that knows where it is, can plan a path from its current location to its goal destination and can avoid colliding with obstacles.

32. AI Robotics Terms Telepresence: –The reduction of cognitive fatigue and simulator sickness by making the human- robot interface more natural: virtual reality. Telemanipulator: –Sophisticated mechanical linkage which translates motions on one end of the mechanism to motions at the other end.

33. AI Robotics Terms Industrial manipulator: –A reprogrammable multifunctional mechanism that is designed to move materials, parts, tools, or specialized devices. Black factory: –A factory that has no lights turned on because there are no workers.

34. Architecture Evaluation Criteria Support for modularity: –Good software engineering principles? Niche targetability: –Works well for the intended application? Ease of portability: –Works for other applications or other robots? Robustness: –Is the system vulnerable? Where?

35. Model S Telemanipulator

37. Movemaster Robot

38. Industrial Robots

39. Robotic Paradigms 1.Hierarchical. 2.Reactive. 3.Deliberative/Reactive.

40. Defining Paradigm Assumptions By the relationship between the primitives. By the way sensor data is processed and distributed.

41. Global World Model Problems Constructing generic global world models is very hard due to the frame problem and the closed world assumption.

42. Global World Model Problems Frame problem: –Deals with the representation of real-world situations in a way that is computationally tractable. Closed/Open world assumption: –States that the world model contains everything the robot needs to know (Closed) and if it is violated the robot may not be able to function correctly.

43. Hierarchical Paradigm Oldest paradigm. Prevalent from 1967-1990. Robot operates top-down. Emphasizes planning. Assumes thought is introspective. A global model captures all sensing data.

44. Hierarchical Paradigm PrimitivesInputOutput SenseSensor dataSensed information PlanSensed and/or cognitive information Directives ActSensed information/ directives Actuator commands

45. Hierarchical Paradigm

46. Robot Control and Operation Section 1.4.2 – 1.7 George Ragousis

47. 4 Ways to control and operate a robot 1. Remote control (RC) 2. Tele-operation 3. Semi-autonomous 4. Autonomous (AI)

48. 1. Remote control –you control the robot –you can view the robot and it’s relationship to the environment –operator isn’t removed from scene, not very safe –ex. radio controlled cars, bomb robots Boxing RC robots 

49. 2. Teleoperation –you control the robot –you can only view the environment through the robot’s eyes –don’t have to figure out AI

50. 2. Teleoperation Display Control Sensor Mobility Effector Power Communi- cation Local Remote Local Remote

51. 2. Teleoperation is suitable for applications where… the tasks are unstructured and not repetitive the task workspace cannot be engineered to permit the use of industrial manipulators key portions of the task require dexterous manipulation, especially hand-eye coordination, but not continuously key portions of the task require object recognition or situational awareness the needs of the display technology do not exceed the limitations of the communication link (bandwidth, time delays) the availability of trained personnel is not an issue

52. 2. Teleoperation Disadvantages… Cognitive fatigue, 100% guidance Simulator sickness communications bandwidth (telepresence) Time delays (Darkstar 1 – Darkspot 0)

53. 3. Semi-autonomous Portion of directions and commands is given to robot 2 flavors Shared control Control trading step by step instructions commanding robot to do something to accomplish task but no within its abilities and allowing the full guidance is required robot to get it done without interaction

54. 4. Autonomous Auto – nomous auto = self nomos = rule self-commanded space robotics the need for autonomy artificial intelligence (AI)

55. Teleoperation Vs Autonomous remote operation Vs self operation much more difficult to achieve higher risk of misjudgment and false actions from robot no time delays in operation independent goal of autonomy and AI: To mimic the capabilities of animals or humans sufficiently in order to survive for long periods with only simple instructions from earth. easy to achieve human in control – small chances of decision and judgment errors dexterous manipulations critical decisions by human (Mars Pathfinder accident) Introduces time delays in proportion with the distance between local & remote.

56. Artificial Intelligence Seven areas 1.Knowledge representation – how am I me? 2.Understanding natural language (willing spirit – weak flesh) 3.Learning 4.Planning & problem solving 5.Inference – just take a decision 6.Search 7.Vision

57. Section 2.1 – 2.2.3 Sylvester Delano

58. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.358 The Hierarchical Paradigm Describe the Hierarchical Paradigm in terms of the 3 robot primitives and its organization of sensing Name and evaluate one representative Hierarchical architecture in terms of: support for modularity, niche targetability, ease of portability to other domains, robustness Understand precondition, closed world assumption, open world, frame problem List two advantages and disadvantages of the Hierarchical Paradigm Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

59. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.359 Organization PLANSENSEACT Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary World model: 1.A priori rep 2.Sensed info 3.Cognitive

60. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.360 Stanford Research Institute ● SRI is an independent, non-profit research institute conducting client-sponsored research and development for government agencies, commercial businesses, foundations, and other organizations. ● SRI is well known for its innovations in communications and networks, computing, economic development and science and technology policy, education, energy and the environment, engineering systems, pharmaceuticals and health sciences, homeland security and national defence, and materials and structures.

61. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.361 Shakey The first mobile robot to be able to reason about its own actions, Shakey combined research in robotics, artificial vision, and natural language processing. Built by SRI (Stanford Research Institute) for DARPA 1967-9 Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

62. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.362 Shakey(cont'd) Programming was primarily in LISP. Used Strips as main algorithm for controlling what to do

63. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.363 What is LISP(LIST Processing) ? A high-level programming language used for developing AI applications. Developed in 1960 by John McCarthy, its syntax and structure is very different from traditional programming languages. For example, there is no syntactic difference between data and instructions. LISP is available in both interpreter and compiler versions and can be modified and expanded by the programmer. Many varieties have been developed, including versions that perform calculations efficiently.

64. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.364 Strips: Means-ends analysis Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary INITIAL STATE:Tampa, Florida (0,0) GOAL STATE:Stanford, California (1000,200) Difference:1020 miles “Go to Stanford AI Lab”

65. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.365 Difference Table d<=200 milesFLY 100<d<200TRAIN d<=100DRIVE Distance (difference) mode of transportation (OPERATOR) d<1WALK Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary mode=difference_table(INITIAL STATE, GOAL STATE, difference) 1.Look up what to do: FLY 2.Not at SAIL, so repeat 3.Look up what to do: DRIVE

66. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.366 Preconditions d<=200 milesFLY 100<d<200TRAIN d<=100DRIVE (rental) DRIVE (personal car) difference OPERATOR d<1WALK Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary How do I know if I’m at the airport or at home? Now must keep up with the state of the world at airport at home PRECONDITIONS

67. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.367 Maintaining State of the World: Add and Delete Lists d<=200 miles FLY 100<d<2 00 TRAIN d<=100DRIVE (rental) at airport DRIVE (personal) at home distanceOPERATORPRE- CONDITIONS d<1WALK Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary at city Y at airport at city Y at train station ADD-LIST at city X DELETE- LIST

68. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.368 Class Exercise Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary d<=200 miles FLY 100<d<2 00 TRAIN d<=100DRIVE (rental) at airport DRIVE (personal) at home distanceOPERATORPRE- CONDITIONS d<1WALK at city Y at airport at city Y at train station ADD-LIST at city X DELETE- LIST

69. Introduction to AI Robotics (Team ONE) Chapter2 Section 2.1 -2.2.369 Strips Summary Designer must set up –World model representation –Difference table with operators, preconditions, add & delete lists –Difference evaluator Strips assumes closed world –Closed world: world model contains everything needed for robot (implication is that it doesn’t change) –Open world: world is dynamic and world model may not be complete Strips suffers from frame problem –Frame problem: representation grows too large to reasonably operate over Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

70. Section 2.2.4 –2.7 Alexander Torres

71. Team One – Hierarchy STRIPS Summary Designer must set up –World model representation –Difference table with operators, preconditions, add & delete lists –Difference evaluator Strips assumes closed world –Closed world: world model contains everything needed for robot (implication is that it doesn’t change) –Open world: world is dynamic and world model may not be complete Strips suffers from frame problem –Frame problem: representation grows too large to reasonably operate over

72. Team One – Hierarchy Closed World Assumption and the Frame Problem It is impractical for a programmer to come up with all possible reactions, conditions to all probable cases in the real world The need to formally represent the world and then maintain every change about it is nonnutritive. The axioms (facts) that would frame the world would quickly become too numerous for any realistic domain A proposed solution was ABStrips which divided the problem into multiple layers of abstraction (this would mean solving problems with increasing levels of details)

73. Team One – Hierarchy Nested Hierarchical Controller (NHC) Representative Architecture Nested Hierarchical Controller (NHC) SENSE PLAN ACT The robot gathers observation from its sensors and combines that information with priori knowledge to create the World Model. From the World Model, the robot can PLAN what action it should take.

74. Team One – Hierarchy Nested Hierarchical Controller (NHC) Representative Architecture Planning for navigation consists of three step executed by Mission Planner, Navigator, and Pilot Each of these can access the World Model The last step is the Pilot module generating specific actions for the robot to do.

75. Team One – Hierarchy Nested Hierarchical Controller (NHC) The Benefits of the NHC are: Unlike STRIPS it interleaves planning and acting It can adapt to changes in its environment if necessary The Disadvantages of NHC are: Planning Function is only appropriate for navigation tasks

76. Team One – Hierarchy NIST REAL Time Control System RCS Real-time Control System Architecture Created by Jim Albus Best suited for semi-autonomous control Based on NHC, RCS is developed as a guide for manufacturers who wish to add AI to their robots. Sensory perception modules introduce a useful preprocessing step between the sensor and the fusion into a world model The Value Judgment module simulates the plan to ensure they work. Behavior Generation Module operates similar to the pilot with less focus on navigations.

77. Advantage Provides an ordering of the relationship between sensing, planning, and acting. Disadvantages Planning, every update cycle the robot would have to update a global world model and do some type of planning. Sensing and action are disconnected. This doesn’t allow for reflexive reactions found in real life. Dependence on global world model is related to the frame problem. A simple task can becomes incredibly complicated to describe. Uncertainty in semantics, sensor noise and actuator errors. Team One – Hierarchy Advantages and Disadvantages

78. Predicate logic and recursion used by STRIPS favors languages such as LISP and PROLOG Although LISP and PROLOG do not have good real-time control properties, the alternative at the time was FORTRAN IV which did not support recursion Hierarchical Paradigm forces programming for specific tasks instead of object oriented tasks. NHC and RCS decomposition of a task is not modular in design Team One – Hierarchy Programming Considerations

79. Team One – Hierarchy Summary Except for NIST Real-time Control Architecture, Hierarchical Paradigm has fallen out of favor for more biologically based systems of control. It has contributed concepts and terminology such as preconditions, closed/open world assumptions, and the frame problem It has the inherent property to allow an evolution of intelligence from semi- autonomous control to full autonomy.