1. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm1 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 Solve a simple navigation problem using STRIPS (hint: work through Sec. 2.2.2) 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

2. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm2 Organization PLANSENSEACT Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary World model: 1.A priori rep 2.Sensed info 3.Cognitive

3. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm3 Shakey First AI robot Built by SRI (Stanford Research Institute) for DARPA 1967-9 Used Strips as main algorithm for controlling what to do Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

4. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm4 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”

5. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm5 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

6. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm6 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

7. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm7 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

8. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm8 Class Exercise Write down the world model, the operator applied, the change in world state, etc. to go from Tampa to Stanford 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

9. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm9 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

10. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm10 Architecture provides a principled way of organizing a control system. However, in addition to providing structure, it imposes constraints on the way the control problem can be solved [Mataric] describes a set of architectural components and how they interact [Dean & Wellman] Types of architectures [Levis, George Mason University] –operational architecture: describes what the systems does, not how it does it –systems architecture: describes how a system works in terms on major subsystems –technical architecture: implementation details Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

11. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm11 Evaluating an Architecture support for modularity: does it show good software engineering principles? niche targetability: how well does it work for the intended application? ease of portability to other domains: how well would it work for other applications or other robots? robustness: where is the system vulnerable, and how does it try to reduce that vulnerability? Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

12. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm12 Hierarchical Paradigm… Top-down: –Plan, plan, plan Control-theoretic: –must measure error in order to control device Planning means: –dependence on world models

13. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm13 Nested Hierarchical Controller (Meystel) Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

14. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm14 NHC Planner Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

15. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm15 RCS (Albus) the hierarchy how the hierarchy works for navigation how it is implemented –nodes and modules –planning time periods

16. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm16 Examples of RCS Apps Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

17. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm17 RCS-4 Levels 7Battalion2-24h 6Platoon5m-2h 5Section1-10m 4Individual Vehicle5-50s 3Subsystem Level200-500ms 2Primitive Level50-500ms 1Servo Level5-50ms

18. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm18 Each Level has a RCS Node Sensory Processing, World Modeling, Behavior Generation, Value Judgment Sensory Processing, World Modeling, Behavior Generation, Value Judgment Engineering of Mind, Albus & Mystel, 2001

19. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm19 Implementation View: Nodes are Recursive

20. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm20 Demo III XUV http://museum.nist.gov/exhibits/timeline/item.cfm?itemId=38 Experimental Unmanned Vehicle in action at Ft. Indiantown Gap. Photo courtesy of the Army Research Labs. Nov. 2001

21. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm21 Demo III Control Hierarchy PLANNER vehicle1 vehicle2 VEHICLE PLANNER communications plan AM plan RSTA plan AM PLANNER Driver Plan Gaze plan COMMS PLANNER message list RSTA PLANNER gaze plan DRIVER PLANNER Velocity Plan GAZE PLANNER Stereo Gaze Plan LADAR Gaze Plan VELOCITY PLANNER F Wheels R Wheels F Steer R Steer F WheelR WheelF Steer Servo 50ms Primitive 500ms Subsystem 5s Vehicle 1m Section 10m

22. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm22 RCS XUV Example Vehicle Level: AM Plan (A1…A10) Primitive Level: Driver Plan (D1…D10)

23. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm23 t=0.5 Primitive Level: Driver Plan extends to A2

24. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm24 t=1 s Obstacle Detected Primitive Level: Driver Plan new waypoints Vehicle Level: detects too large a variation

25. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm25 t=1 s Vehicle Level Planner Opt 1 Vehicle Level: new AM Plan Primitive Level: new Driver Plan

26. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm26 t=3 More obstacle is seen… fail upwards again Vehicle Level: new AM Plan Primitive Level: new Driver Plan

27. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm27 t=4.5s Vehicle Level: new AM Plan skip A1, go to A2 Primitive Level: new Driver Plan

28. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm28 t=6 s Vehicle Level: new AM Plan skip old A2 Primitive Level: new Driver Plan

29. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm29 Exercise: Adapt to Rescue Robots? PLANNER vehicle1 vehicle2 VEHICLE PLANNER communications plan AM plan RSTA plan AM PLANNER Driver Plan Gaze plan COMMS PLANNER message list RSTA PLANNER gaze plan DRIVER PLANNER Velocity Plan GAZE PLANNER Stereo Gaze Plan LADAR Gaze Plan VELOCITY PLANNER F Wheels R Wheels F Steer R Steer F WheelR WheelF Steer Servo 50ms Primitive 500ms Subsystem 5s Vehicle 1m Section 10m

30. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm30 Nodes are made from Modules uff applies rule (transition rules) sensors actions u=uff+G(xd-x*) u is control action x* is predicted world state xd is desired world state uff is the feedforward control plan transform into x* G is feedbackxd is from “above”

31. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm31 Nodes are made from Modules uff applies rule (transition rules) sensors actions if BALL, move toward centroid if NOT BALL, turn clockwise (feedback determines how fast) transform into x* G is feedbackxd is from “above”

32. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm32 Nodes are made from Modules uff applies rule (transition rules) sensors actions if BALL, move toward centroid if NOT BALL, turn clockwise (feedback determines how fast) transform into x* G is feedbackxd is from “above” when to stop? how far is far enough? what about noise/fuzzy ball? … sensor noise, actuator error, rigid models

33. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm33 Advantages of Hierarchies Albus and Mystel 01: Natural way to organize Not intrinsically rigid Not intrinsically inefficient –not the same as centralized planning –priorities and goals are clear, therefore efficient

34. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm34 Summary RCS hierarchy with node structure at each level –have operator interface (in theory) nodes consist of –Sensory Processing –World Model –Behavior Generation –Value Judgment top-down, plan for a particular horizon –control theoretic

35. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm35 Evaluating the Two Architectures support for modularity: –decomposition by functionality niche targetability: –good, both have been used for apps like vehicle guidance, mining equipment ease of portability to other domains: –unclear, not sure if code could be reused—lots of rewriting on previous apps robustness: –RCA simulates plans in advance, but not sure what it would do with sensor or mechanical failures, etc. Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary

36. 2 Introduction to AI Robotics (MIT Press)Chapter 2: The Hierarchical Paradigm36 Hierarchical Review Describe the hierarchical paradigm in terms of the three robot primitives Describe sensing in the hierarchical paradigm What is STRIPS? What is the closed world assumption? What are preconditions? What is the frame problem? What are two representative architectures? What is the NHC decomposition? Organization -SPA -global Strips -Shakey Rep. Arch. -evaluation -NHC -RCA Summary