16-311 Intro. to Robotics

1. 16-311 Intro. to Robotics Sensing and Sensors Steve Stancliff

2. Credits • Much borrowage from Mel Siegel’s 16-722 slides • “Ranging Sensors” section from the old 16-311 slides by: • Sean Pieper • Bob Grabowski • Howie Choset

3. Outline • Why Sense? • Senses / Sensors • Transduction • Interfacing - Hardware • Interfacing - Software • References

4. Why Sense? • Why not just program the robot to perform its tasks without sensors? • Uncertainty • Dynamic world • Detection / correction of errors

5. Human Sensing What sensed: • EM waves • Pressure waves • Chemicals - flavor • Chemicals - odor • Contact pressure Sense: • Vision • Audition • Gustation • Olfaction • Tactition

6. Human Sensing Sense • Thermoception • Nociception • Equilibrioception • Proprioception What sensed: • Heat • Pain • Sense of balance • Body awareness

7. Animal Sensing • Magnetoception (birds) • Electroception (sharks, etc.) • Echolocation (bats, etc.) • Pressure gradient (fish)

8. Human Sensors Sensor: • Eyes • Ears • Tongue • Nose • Skin Sense: • Vision • Audition • Gustation • Olfaction • Tactition

9. Human Sensors Sense: • Thermoception • Nociception • Equilibrioception • Proprioception Sensor: • Skin • Skin, organs, joints • Ears • Muscles, joints

10. Robot Sensors Sensor: • Camera • Microphone • Chemical sensors • Chemical sensors • Contact sensors • Thermocouple • ? Sense: • Vision • Audition • Gustation • Olfaction • Tactitions • Thermoception • Nociception

11. Robot Sensors Sensor: • Accelerometer • Encoders • Magnetometer • Voltage sensor • Sonar • Array of pressure sensors? Sense: • Equilibrioception • Proprioception • Magnetoception • Electroception • Echolocation • Pressure gradient

12. Robot Sensors • EM spectrum beyond visual spectrum • (RADAR, LIDAR, radiation, infrared) • Chemical sensing beyond taste and smell • Hearing beyond human range • Lots more.

13. Gas Piezo Bend GPS Resistive Bend Lever Switch Camera Pressure Accelerometer Rotary Encoder Magnetic Reed Switch Gyroscope Pyroelectric Detector Linear Encoder Sonar Ranging IR Modulator Receiver Laser Rangefinder UV Detector PIR CDS Cell Magnetometer Radiation Infrared Ranging Compass Robot Sensors – A Sampling Pendulum Resistive Tilt Metal Detector Microphone

14. Transduction • What do all of these sensors have in common? • They all transduce the measurand into some electrical property (voltage, current, resistance, capacitance, inductance, etc.)

15. Transduction • Many sensors are simply an impedance (resistance, capacitance, or inductance) which depends on some feature of the environment: • Thermistors: temperature  resistance • Humidity sensors: humidity  capacitance • Magneto-resistive sensors: magnetic field  resistance • Photo-conductors: light intensity  resistance

16. Transduction • Other sensors are fundamentally voltage sources: • Electrochemical sensors: chemistry  voltage • Photovoltaic sensors: light intensity  voltage

17. Transduction • Still other sensors are fundamentally current sources: • Photocell : photons/second  electrons/second • Some sensors collect (integrate) the current, outputting electrical charge: • CCD: photons  charge

18. Interfacing - Hardware • How can we interface each of these types of signals to a computer? • Voltage • Compare to a reference voltage • Current • Pass it through a reference resistor, measure the voltage across the resistor • Resistance • Use a fixed resistor to make a voltage divider, measure the voltage across one of the resistors

19. Interfacing - Hardware • Voltage • Compare to a reference voltage • Most microcontroller boards have 0-5V input lines. The 5V reference is internal to the board. • If your device outputs a voltage higher than the input range, use a voltage divider to measure a fraction of it.

20. Interfacing - Hardware • Voltage divider: Figure from http://hyperphysics.phy-astr.gsu.edu/hbase/electric/voldiv.html

21. Interfacing - Hardware • Current: • Pass it through a reference resistor, measure the voltage across the resistor Figure from http://digital.ni.com/public.nsf/allkb/82508CD693197EA68625629700677B70

22. Interfacing - Hardware • Resistance: • Use a fixed resistor to make a voltage divider, measure the voltage across one of the resistors Figure from http://www.kpsec.freeuk.com/vdivider.htm

23. Interfacing – Hardware • Higher-level interfacing. • Complicated sensors (cameras, GPS, INS, etc.) usually include processing electronics and provide a high-level output (USB, firewire, RS-232, RS-485, ethernet, etc.)

24. Interfacing - HB • Handy Board input ports: Source: “The Handy Board Technical Reference”, Fred G. Martin, 2000.

25. Interfacing - HB • Handy Board input connector: • Input port has 47k pull-up resistor. When nothing is connected, it will read +5V Source: “The Handy Board Technical Reference”, Fred G. Martin, 2000.

26. Interfacing - HB • Digital sensor: • Switch pulls input down to ground when closed. Source: “The Handy Board Technical Reference”, Fred G. Martin, 2000.

27. Interfacing - HB • Resistive sensor: • Sensor forms voltage divider with internal pull-up resistor. Source: “The Handy Board Technical Reference”, Fred G. Martin, 2000.

28. Interfacing - Software • Calibration • For many sensors you want to calibrate a maximum and minimum and/or a threshold value. • Those values can be subject to ambient conditions, battery voltage, noise, etc. • You need to be able to easily calibrate the sensor in the environment it will operate in, at run time.

29. Interfacing - Software • Ex: Calibrating a light sensor: • Perhaps you want to calibrate the brightest ambient light value. • For instance, in the Braitenberg lab, if you know the brightest ambient value, then anything brighter than that is the goal.

30. Interfacing - Software • Ex: Calibrating a light sensor: • Manual calibration: • Robot prints light sensor readings to the LCD. • Move it around until you find the maximum. • Press a button to store those values. • Automatic calibration: • Robot moves around the room • (spin in place? drive around randomly?) • Stores the highest value it encounters.

31. Interfacing - Software • Ex: Calibrating an encoder (for a device with a limited range of motion): • Manual calibration: • Move the device to one end of the motion. • Press a button to record that position. • Move the device to the other end of the motion. • Press a button to record that position. • Automatic calibration: • Robot moves the device in one direction until it hits a limit switch. Records that value. • Then moves in the other direction until it hits another limit switch. Records that value.

32. Interfacing - Software • Signal conditioning. • For many sensors if you just take the values straight from the hardware you will get erratic results. • Signal conditioning can be done in hardware or software. Often both are used. We’ll talk about software methods here.

33. Interfacing - Software • Signal conditioning – averaging. • With a light sensor or a range sensor, you may want to average several readings together. • This will reduce errors that are equally distributed above and below the true value.

34. 50 μs stable bouncing stable Interfacing - Software • Signal conditioning – debouncing. • When a switch is pressed, the mechanical contacts will bounce around briefly. The electrical signal looks something like this: Figure from slides for 16-778 Mechatronic Design.

35. Interfacing - Software • Signal conditioning – debouncing. • The result is that your program may think that the switch was pressed multiple times. • One easy way to debounce in software is to only read the sensor value periodically, with a period larger than the settling period for the switch. • In the previous slide, the settling period was 150ms • The downside to this method is that it reduces the rate at which you can read real changes.

36. Ranging Sensors • Intensity-based infrared:

37. Ranging Sensors • Intensity-based infrared: • Easy to implement (few components) • Works very well in controlled environments • Sensitive to ambient light Increase in ambient light raises DC bias voltage time voltage time

38. amplifier bandpass filter integrator limiter demodulator comparator Input Output 600us 600us Ranging Sensors • Modulated infrared: http://www.hvwtechnologies.com http://www.digikey.com

39. Ranging Sensors • Modulated infrared: • Insensitive to ambient light • Built in modulation decoder (typically 38-40kHz) • Used in most IR remote control units ( good for communications) • Mounted in a metal Faraday cage • Cannot detect long on-pulses • Requires modulated IR signal

40. Optical lenses +5v output input 1k 1k gnd Ranging Sensors • Digital infrared:

41. Ranging Sensors • Digital infrared: • Optics to covert horizontal distance to vertical distance • Insensitive to ambient light and surface type • Minimum range ~ 10cm • Beam width ~ 5deg • Designed to run on 3v -> need to protect input • Uses shift register to exchange data (clk in = data out) • Moderately reliable for ranging

42. Ranging Sensors • Polaroid ultrasonic: http://www.robotprojects.com/sonar/scd.htm

43. Ranging Sensors • Polaroid ultrasonic: • Digital Init • Chirp • 16 high to low • -200 to 200 V • Internal Blanking • Chirp reaches object • 343.2 m/s • Temp, pressure • Echoes • Shape • Material • Returns to Xducer • Measure the time

44. Ranging Sensors • Problems: • Azimuth uncertainty • Specular reflections • Multipass • Highly sensitive to temperature and pressure changes • Minimum range

45. Ranging Sensors • Naive sensor model

46. Ranging Sensors • Problem with naive model:

47. Ranging Sensors • Problem with naive model:

48. Ranging Sensors • Reducing azimuth uncertainty: • Pixel based methods (most popular) • Region of constant depth • Arc transversal method • Focusing multiple sensors

49. Ranging Sensors • Certainty grid approach: • Combine info with Bayes rule • (Moravec and Elfes)

50. Ranging Sensors • Arc transversal method: • Uniform distribution on arc • Consider transversal intersections • Take the median