1. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation1 Designing a Reactive Implementation List the steps involved in designing a reactive behavioral system. Use schema theory to program behaviors using object- oriented programming principles. Design a complete behavioral system, including coordinating and controlling multiple concurrent behaviors. Describe the two methods for assembling primitive behaviors into abstract behaviors: finite state machines and scripts. Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

2. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation2 Steps in Designing a Reactive Behavioral System Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

3. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation3 CSM 1994 UGV Competition Fully autonomous vehicle, all on-board, navigate a course 10ft wide, about 800ft long Obstacles Carry a 20 pound payload (this is from 1996, but it’s a way better picture) Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

4. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation4 1-3. Describe the Task, Robot, Environment Have to use computer vision… black &white, slow processor speeds (didn’t get to design the robot) –White (bright) should be in the center of the image –Reflections on grass are white, but random so average out If stay in middle, never encounter an obstacle! 150ms update rate needed for steering to stay in control at ~1.5mph Camcorder on a Panning mast, going to A framegrabber Sonar on a panning mast 33MHz 486 PC running Lynx (commercial unix) Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

5. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation5 4. Describe how robot should act Follow the line and stay in the middle –Follow-line –Only need the Camcorder! Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

6. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation6 5-6 Refine and test each behavior Follow-line –Worked with toilet paper (indoors), –Worked with athletic line tape (outdoor) Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

7. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation7 7 Test with other behaviors “Full dress rehearsal” –Oops, bales of hay are bright compared to grass, change the centroid to cause collision Go back to step 4: –Follow line until “see” an obstacle, then just go straight until things return to normal Hard to do visually in real time Sonar! Look to the side and when something is close, it’s a bale, so go straight Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

8. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation8 Final System Round 1 –OOPS: sonar connection off so it hit the bale Round 2 –White shoes and dandelions, plus Killer Bale Demo round –Hill vs. implicit flat earth assumption Round 3 –Trapped by sand, but $5K richer! Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

9. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation9 Main Points Let the WORLD BE ITS OWN BEST REPRESENTATION and CONTROL STRUCTURE –“line” wasn’t a “line” just centroid of brightest pixels in the image –Pick up trash: if can is in gripper, then go to the recycle bin Design process was iterative; rarely get a workable emergent behavior on the first try There is no single right answer Could have been done with subsumption, pfields, rules, whatever Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

10. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation10 Other Lessons Learned Don’t count on getting much work done in the field! “A river runs through it…” Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

11. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation11 Case Study and Field Trip: Polar Robotics Existing robots –DANTE, DANTE II –Nomad

12. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation12 DANTE Task –explore volcanoes in Antarctica (reduce risk to vulcanologists) Environment –steep, rocky slopes Robot –legged “framewalker” Behaviors –rappel down Refine and test Test with other behaviors –1997 South America, failed –1998 Antarctica, med. success

13. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation13 Lessons to Be Learned A robot is part of a system, must design system –example tether breaking Testing and evaluation really does take ~30% of the time allocated (just like software engineering) –and more to fix the problem NASA technical readiness levels –Level 1: just an idea –Level 6: demonstrated on a realistic test bed –Level 9: has flown, fully operational

14. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation14 Nomad Task –search for and analyze meteorities Environment –Antarctica Robot –hybrid mobility, LADAR, omnivision, sample sensors Behaviors –search an area using GPS, avoid obstacles, stop at possible meteorities and alert user. Can be controlled by human Refine and Test Test with other behaviors –1999 –2000 success

15. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation15 Nomad Omnivision

16. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation16 Hyperion (really about Mars) Task –navigate Arctic Environment –Arctic Robot –wheeled, uses solar Behaviors Refine and test Test with other behaviors –2002 success

17. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation17 NASA HMP / Mars Society Flashline Project Robotics Support Confined space inspection of Mars habitat Marsupial deployment for fault identification Human robot team for collaborative exploration of hazardous areas & narrow fissures in search of micro-organisms

18. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation18 Case Study in Pfields: Docking Needed for marsupial robots Note – use of reactivity –simple perception –pfields –improvement over human

19. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation19 Daughter-centric Docking Behavior Potential field methodology: orientation, Xbar= tangent vector overall size= attraction vector (Arkin, Murphy 90) Silver Bullet: AMD K-6 400MHz clearance=+/-2cm +/-5 degrees Bujold: Inuktun mVGTV Pan only, color camera, optics at about 2ms, skid steering, no on-board processor

20. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation20 Docking Behavior Results Pfields weren’t intended to work behind the gate Optics dictated 120 deg, 2m Approach Zone 48 data points (3 per 16 stations) on time to completion –by angle –by radial position Larger angles, the slower, and farther away the slower 2 failures: 3, 7 Fastest: 26 sec. Slowest: 81 sec.

21. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation21 Docking Behavior Results: teleoperation Performance comparison: - 66 data points, 22 teleoperators - paired sample t-test (conf>95%) Communications data: -36 data points, 6 teleoperators Teleoperators did better only at 1,3 where the robot wasn’t supposed to be able to dock from. Noticed that teleoperators used a different strategy; opportunity for improvement 17% faster

22. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation22 Docking Vision Spherical Coordinate Transform space instead of HSV, RGB Biomimetic vision: gradient, looming O(m x n) lighting insensitive color segmentation 8-10 frames/sec on commercial hardware vs. 30 frames/sec for Cognachrome hardware Robust algorithm –2-colored landmark to prevent confusion –imprinting and time of day look up tables (LUT) –if time-out, mother moves a color is a circle on the plane

23. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation23 Initial values Compute region statistics new values for region Light insensitive color segmentation ImprintAdapt Extract regions Perform connected components >15 tries LUT (time of day, weather)

24. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation24 Indoor Data Collection and Demonstrations

25. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation25 Outdoor Demonstrations Imprint at dawn (light mist), return 6 hours later As expected, mediocre performance from dusk to night (~50%) due to headlight reflection

26. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation26 Additional Case Studies: Commercial Products Robomow –cutting grass in residential areas My Real Baby –toy dolls

27. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation27 Robomow Behaviors? Random Avoid –Avoid(bump=obstacle) –Avoid(wire=boundary) Stop –Stop(tilt=ON) All active www.friendlymachines.com Overview History Reactive USAR Summary

28. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation28 My Real Baby Behaviors? Touch-> Awake Upside down & Awake-> Cry Awake & Hungry -> Cry Awake & Lonely -> Cry Note: can get crying from multiple behaviors Note: internal state (countdown timer on Lonely) www.irobot.com Overview History Reactive USAR Summary

29. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation29 Commercial Case Studies Purely reactive May not need subsumption or pfields, very straightforward State of practice is much less complicated than state of the art!

30. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation30 Design Tool: Behavior Table An agent is attracted to light. If it sees light, it heads in that direction. If it encounters an obstacle, it turns either left or right, favoring the direction of the light. If there is no light, it sits and waits. But if an obstacle appears, the agent runs away. 1. photropism 2. Obstacle avoidance Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

31. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation31 Behavior Table ReleaserBehaviorMotor Schema PerceptPerceptual Schema Lightphototropismmove2Light() :Attraction Light: direction & strength Brightest(di r), atLight() Range Obstacle avoidance avoid(): turn left or right; runaway() proximityObstacle() An agent is attracted to light. If it sees light, it heads in that direction. If it encounters an obstacle, it turns either left or right, favoring the direction of the light. If there is no light, it sits and waits. But if an obstacle appears, the agent runs away. Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

32. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation32 Assemblages of Behaviors What to do if you have a SEQUENCE of behaviors as well as CONCURRENCY? Two equivalent methods –Finite state automata (FSA) –Scripts –(other ways too) Two approaches: –Stuff the coordination mechanism into a separate controlling program (like a main ()) Hurts portability, adding new behaviors “on top” –Stuff the coordination mechanism into a meta-behavior or abstract behavior using recursive-ness of schemas Coordination mechanism is the coordinated control program part of the behavioral schema Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

33. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation33 Example of a Sequence: Catch Suzy!

34. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation34 Example Continued “Tracking Phase” –move to goal –avoid obstacle “Pick up Phase” –fine position –pick up “Return Home Phase” –move to goal –avoid obstacle same behaviors, just DIFFERENT INSTANTIATION OF GOAL

35. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation35 FSA: M={K, , ,s,F} K: all the states, each is “q”- behaviors  : transition function,  (q,  )= new behavior  : inputs that agent can “see”, each is  – stimulus/affordances q 0 : Start state(s)- part of K F: Terminating state(s)- part of K Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

36. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation36 FSA Summary “State” doesn’t mean “state of world” (bad); it means more “where the innate releasing mechanism is currently at” Advantages –Formal mechanism –Have to fill in the table, so a way of spotting unforseen effects Disadvantages –Hard to keep up with implicit behaviors Ex. Avoid obstacle is often running throughout ALL states, gets tedious to express it formally –Tend to add explicit variable for transitions, rather than rely on emergent behavior from environment Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

37. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation37 Scripts UGV competition really didn’t have a sequence of behaviors, just toggling back and forth USAR victim detection has more of a typical sequence or order of behaviors (like digger wasps mating) Imagine trying to do an FSA for the USAR task Scripts are equivalent to FSA but may be more natural or readable for sequences Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

38. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation38 Scripts ScriptBehavior AnalogExamples GoalTaskFind victims in rubble PlacesEnvironment, applicability or “taskability” for new tasks Collapsed buildings ActorsBehaviorsexplore(), dance(), avoid(), crawl, move2void, move2victim Props, cuesPerceptsVoids: Dark, concave Victims: heat, motion, color Causal Chain Sequence of behaviorExplore, dance, move2void, crawl, move2victim, dropRadio SubscriptsException handlingIf lose communications, return home Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

39. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation39 Scripts Summary Advantages –A more storyboard like way of thinking about the behaviors –If-then, switch style of programming like FSA –Since a Script is “in” a behavior, other behaviors such as avoid can be running concurrently without having to appear “in” the script –Exception handling is a big plus in Real Life Disadvantages –Can be a bit of overkill for simple sequences, especially with C++ Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary

40. 5 Introduction to AI Robotics (MIT Press)Chapter 5: Designing a Reactive Implementation40 Summary Design of reactive systems is similar to design of object-oriented software systems –Highly modular, can test behaviors independently Follows the basic steps in the Waterfall Lifecycle –Describe task, robot, environment, how robot should act, refine behaviors, test independently, test together. –Except lots more iteration, making it more like Spiral Behavior tables can help keep track of what’s a behavior and its releasers and percepts Sequences of behaviors, rather than combinations, can be controlled by a separate routine or by adding a routine to the coordinated control program in the behavioral schema –FSA and Scripts are two main methods Design -Beh. Table -Steps Case Study Coordination -FSA -Scripts Summary