Advanced Robot Control

1. Advanced Robot Control Programming for Robustness with RoboLab FLL Team 16

2. Positioning • Absolute • Uses features or ‘landmarks’ of the course • Relative • Robot keeps track of its moves • Relies on Odometry FLL Team 16

3. Positioning Problems • Absolute • May have difficult time finding small landmarks • Some landmarks & robots are easily damaged • Relative • Error accumulates with every move • If too many errors, robot maybe too far off course to find landmark later FLL Team 16

4. Common Sources of Error • Rotation Sensor Resolution • Gear Backlash • Program Execution Speed • Wheel Spin/Skidding • Inside Turn Wheel FLL Team 16

5. Rotation Sensor Resolution • Robot only knows position with plus or minus one count (at best) • Gear backlash increases error beyond one count • Use finer resolution to reduce error (Minimize Distance per Count) • Rotation sensor should be at same speed as motor (or up to 1-1/2 times higher) FLL Team 16

6. Program Execution Speed • Rotation sensor not read continuously • RCX may not ‘see’ a target • RCX will not react instantly FLL Team 16

7. Wheel Spin at Startup • Caused by sudden application of motor torque, not enough weight on drive wheels • Wheels and rotation sensor turn before robot starts • Skip or changes direction due to “jump” from start FLL Team 16

8. Skidding • Caused by rapid application of motor braking and not enough weight on drive wheels • Robot told to stop but continues to move • Rotation sensor doesn’t ‘see’ move • Sends robot off position, affecting next move by robot FLL Team 16

9. Turns • Errors are magnified in turns • Any slight direction error can cause larger side-to-side error • Braking of inside wheel • Any movement of the inside wheel lessens the overall turn; true angle is shorter than with a locked wheel • Turns made with two counter-rotating wheels doubles rotation sensor resolution errors • Additional errors if wheels don’t turn at same speeds FLL Team 16

10. Set a reasonable speed-Try gearing robot for 10 to 15 inches per second Allows one wheel to be ‘locked’ in turn Gear rotation sensor for 1/8” of travel per count or less Measures position as precisely as practical Minimize backlash by avoiding multi-stage gearing Avoid loose gear meshes Keep weight on driving wheels Gain traction Minimize slipping and skidding Weight shifts with accel/decel Match motors – use two motors with same output speeds Use motor test jig Non-Programming Solutions FLL Team 16

11. Motor Test Jig • Build a motor test jig using: • Load motor with worm geartrain • Test and record motor data • Run for turn, record counts • Forward and reverse • Different power levels Picture of Motor Test Jig FLL Team 16

12. Programming Solutions • ‘Creeping’ • ‘Precise’ Forward/Reverse/Turns • ‘Square Up’ to Lines • Line Following using ‘shades of gray’ • Experimentation FLL Team 16

13. ‘Creeping’ • Moves Robot Slowly by providing a series of taps to the robot • Overcome static friction • Provides braking and speed control • Offers these Advantages • Go slowly to minimize wheel slippage • Minimize distance error due to polling error • Better chance of sensing narrow lines • Bump up against landmark with much less force FLL Team 16

14. Why Not Use Low Power Levels? • Often don’t provide enough power to overcome static friction • Robot still rolls easily enough that speed is still too high FLL Team 16

15. How to Creep • Create a loop to wait for rotation (or time, light level or button press) • Start motors at medium power level • Wait for a very small time (1/100 sec) • Stop the motors • Wait for a very small time (1/100 sec) • End loop FLL Team 16

16. Creep Example FLL Team 16

17. Precise Turns/Forward/Reverse • Power applied gradually • Reduce power before target • Creep forward/backward until reach target FLL Team 16

18. ‘Precise’ Startup • Uses subroutine (to save memory) • Position target passed from main task via container • Sets up intial target • Try using 10 to 20 counts short of actual target • Loops until initial rotation target • Branches to different power levels based on timer to provide smoother acceleration • Avoids wheel slip at startup FLL Team 16

19. FLL Team 16

20. At Initial Target • Coast or Creep • If coasting, coast until time • Could possibly coast past target • Creeping applies pulsed braking • No skidding • Self correcting using closed loop positioning • Moves forward or reverse to final target count • Too far – creeps in reverse • Too short – creeps forward FLL Team 16

21. FLL Team 16

22. One subroutine can be used for left turns and forward Container 7 is set to 0 or 1 to choose left or forward Reverse or right turns are done similarly Stored as subroutines to save memory Target counts are passed using blue container Set container for forward/reverse or left/right Routine Details FLL Team 16

23. Square Up • Line up robot to edge of line • Uses two Light Sensors • Moves robot so each sensor seeks dark/light edge • Know exact spot when parked • Accuracy in direction • Accuracy in position (1 axis) FLL Team 16

24. Square Up ‘Setup’ • Square up to dark line • Each sensor is different • Needs to be set before running • Separate sub-vi that calibrates light levels • Grabs light values • Calculates and stores threshold values FLL Team 16

25. How it works • For each sensor: • If sensor sees: • Light: Creep one pulse forward, Reset Container to 0 • Dark: Add 1 to container • Do until container is set to 2 which means both sensors made it to the dark line • Robot “waddles” to the line • Repeat process with motors set for reverse and looking for light instead of dark • Repeat loop two times to assure exact placement FLL Team 16

26. FLL Team 16

27. Line Following • Follow line edge using light sensor • Reads average value of light within a circle • Seeking halfway between light and dark • Based upon Light level sensed Motor ‘Behavior’ will set motors to creep to steer robot toward line edge • Can be separated into the 7 zones (‘shades of grey’) • Can go straight or turn depending on value • Go faster and straighter near middle zones • Go slower and turn sharper in zones away from middle FLL Team 16

28. FLL Team 16

29. Program Example • Create an outer loop • rotation sensor target • Create a decision tree within the loop • Made with container forks for branching for different response to each light level range • Use Creeping within each branch • Each of the 7 conditions can be setup and tested individually FLL Team 16

30. Experimentation is Key • Alter creep speed and turn radius • Watch robot to see how it behaves • Adjusting height of light sensor • Changes size of circle being read • Changes sensitivity • Adjust location of light sensor • Change weight distribution FLL Team 16

31. Memory Management • Use Subroutines(‘Subs’) for routines called repeatedly • Pass parameters to ‘Subs’ using Containers • Use Containers as flags (for program forks) to get multiple functions per Sub. • Use utility programs to show memory usage and clear out slots. • Get to know memory usage of program elements FLL Team 16

32. Show Memory vi example FLL Team 16

33. Erase Slot vi example FLL Team 16

34. One Final Thought: “The lesson is in the struggle and not in the victory” FLL Team 16