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CMPUT 412 Sensing

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CMPUT 412 Sensing Csaba Szepesv ri University of Alberta TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAAAAAA – PowerPoint PPT presentation

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Title: CMPUT 412 Sensing


1
CMPUT 412Sensing
  • Csaba Szepesvári
  • University of Alberta

TexPoint fonts used in EMF. Read the TexPoint
manual before you delete this box. AAAAAAA
2
Defining sensors and actuators
Environment
Sensations (and reward)
actions
Controller agent
3
Perception
  • Sensors
  • Uncertainty
  • Features

4
How are sensors used?
5
HelpMate, Transition Research Corp.
6
B21, Real World Interface
7
Robart II, H.R. Everett
8
Savannah, River Site Nuclear Surveillance Robot
9
BibaBot, BlueBotics SA, Switzerland
Omnidirectional Camera
Pan-Tilt Camera
IMUInertial Measurement Unit
Sonar Sensors
Emergency Stop Button
Laser Range Scanner
Wheel Encoders
Bumper
10
Taxonomy of sensors
11
Classification of Sensors
  • Where is the information coming from?
  • Inside Proprioceptive sensors
  • motor speed, wheel load, heading of the robot,
    battery status
  • Outside Exteroceptive sensors
  • distances to objects, intensity of the ambient
    light, unique features
  • How does it work? Requires energy emission?
  • No Passive sensors
  • temperature probes, microphones, CCD
  • Yes Active sensors
  • Controlled interaction -gt better performance
  • Interference
  • Simple vs. composite (sonar vs. wheel sensor)

12
General Classification (1)
13
General Classification (2)
14
Sensor performance
15
How Do (Simple) Sensors Work?
Analog signals
Digital signals
16
Mathematical Models
  • Signal in gt signal out response
  • Memoryless Vout S( Ein , Noiset)
  • With memory Vout f( Vout, Ein , Noiset)

Sampling rate, aliasing, dithering
Electrical current
Environment
Physical process
Analog to digital conversion
00101011010100 11010111010101
input
output
17
Nominal Sensor Performance
  • Valid inputs
  • Emin Minimum detectable energy
  • Emax Maximum detectable energy
  • Dynamic range Emax/Emin , or 10 log(Emax/Emin )
    dB
  • power measurement or volt? (V2 power)
  • Operating range (Nmin, Nmax) Emin Nmin Nmax
    Emax
  • No aliasing in the operating range (e.g.,
    distance sens.)
  • Response
  • Sensor response S(Ein)?
  • Linear? (or non-linear)
  • Hysteresis
  • Resolution ()
  • E1-E2 ) S(E1)¼ S(E2) often min(Emin , A/D
    )
  • Timing
  • Response time (range) delay between input and
    output ms
  • Bandwidth number of measurements per second Hz

18
In Situ Sensor Performance Sensitivity
  • Characteristics .. especially relevant for real
    world environments
  • Sensitivity
  • How much does the output change with the input?
  • Memoryless sensors min d/dE S (Ein) Ein
  • Sensors with memory min f(V,Ein)/Ein V, Ein
  • Cross-sensitivity
  • sensitivity to environmental parameters that are
    orthogonal to the target parameters
  • e.g. flux-gate compass responds to ferrous
    buildings, orthogonal to magnetic north
  • Error ²(t) S(t) - S(Ein(t))
  • Systematic ²(t) D(Ein(t))
  • Random ²(t) is random, e.g., ²(t) N(¹,¾2)
  • Accuracy (systemacity) 1-D(Ein)/Ein, e.g.,
    97.5 accuracy
  • Precision (reproducability) Rangeout/
    Var(²(t))1/2

19
In Situ Sensor Performance Errors
  • Characteristics .. especially relevant for real
    world environments
  • Error ²(t) S(t) - S(Ein(t))
  • Systematic ²(t) D(Ein(t))
  • Predictable, deterministic
  • Examples
  • Calibration errors of range finders
  • Unmodeled slope of a hallway floor
  • Bent stereo camera head due to an earlier
    collision
  • Random ²(t) is random, e.g., ²(t) N(¹,¾2)
  • Unpredictable, stochastic
  • Example
  • Thermal noise hue calibration, black level
    noise in a camera
  • Accuracy accounts for systemic errors
  • 1-D(Ein)/Ein, e.g., 97.5 accuracy
  • Precision high precision low noise
  • Rangeout/ Var(²(t))1/2

20
Challenges in Mobile Robotics
  • Systematic vs. random errors
  • Error distributions

21
Systematic vs. Random?
  • Sonar sensor
  • Sensitivity to material, relative positions of
    sensor and target (cross-sensitivity)
  • Specular reflections (smooth sheetrock wall in
    general material, angle)
  • Systematic or random? What if the robot moves?
  • CCD camera
  • changing illuminations
  • light or sound absorbing surfaces
  • Cross-sensitivity of robot sensor to robot pose
    and robot-environment dynamics
  • rarely possible to model -gt appear as random
    errors
  • systematic errors and random errors might be well
    defined in controlled environment. This is not
    the case for mobile robots !!

22
Error Distributions
  • A convenient assumption ²(t) N(0,)
  • WRONG!
  • Sonar (ultrasonic) sensor
  • Sometimes accurate, sometimes overestimating
  • Systematic or random? Operation modes
  • Random gt Bimodal- mode for the case that the
    signal returns directly- mode for the case that
    the signals returns after multi-path reflections.
  • Errors in the output of a stereo vision system
    (distances)
  • Characteristics of error distributions
  • Uni- vs. Multi-modal,
  • Symmetric vs. asymmetric
  • Independent vs. dependent (decorrelated vs.
    correlated)

23
About Some Sensors
  • Wheel Encoders
  • Active Ranging

24
Wheel Encoders
25
Wheel/Motor Encoders (1)
  • Principle Photo detection optical grid
  • Direction of motion Quadrature encoder
  • Output Read values with polling or use
    interrupts
  • Resolution 2000 (-gt10K) cycles per revolution
    (CPR).
  • for higher resolution interpolation, sine waves
  • Accuracy no systematic error (accuracy100)

time
26
Wheel/Motor Encoders (2)
  • Measures position or speed of the wheels or
    steering
  • Use odometry, position estimation, detect
    sliding of motors

27
Active Range Sensors
28
Range Sensors
  • Large range distance measurement
  • -gt range sensors
  • Why?
  • Range information is key for localization and
    environment modeling
  • Cheap
  • Relatively accurate
  • How?
  • Time of flight
  • Active sensing (sound, light)

29
Time of flight - principles
  • Time delay of arrival (TDOA)
  • TDOA impulses
  • Sound, light
  • TDOA phase shift
  • Light
  • Geometry
  • Triangulation single light beam
  • Light
  • Triangulation structured light
  • Light
  • Light sensor 1D or 2D camera

30
Time Delay of Arrival
  • d v t
  • d distance travelled (computed)
  • v speed of propagation (known)
  • t time of flight (measured)

31
TDOA Limitations
  • What distances can we measure?
  • Must wait for the last package to arrive before
    sending out the next onegt Speed of propagation
    determines maximum range!
  • Speeds
  • Sound 0.3 m/ms
  • Electromagnetic signals (lightlaser) 0.3
    m/ns, 1M times faster!
  • 3 meters takes..
  • Sound 10 ms
  • Light 10 ns.. But technical difficulties gt
    expensive and delicate sensors

32
TDOA Errors
  • Time measurement
  • Exact time of arrival of the reflected signal
  • Time of flight measure (laser range sensors)
  • Opening angle of transmitted beam (ultrasonic
    range sensors)
  • Interaction with the target (surface, specular
    reflections)
  • Variation of propagation speed
  • Speed of mobile robot and target (if not at stand
    still)

33
Ultrasonic Sensor
34
Ultrasonic (US) Sensor
  • transmit a packet of US pressure waves
  • The speed of sound v (340 m/s) in air is
  • adiabatic index (sound wave-gtcompression-gtheat
    )
  • R moral gas constant J/(mol K)
  • M molar mass kg/mol
  • T temperature K

35
Operation
Wave packet
Transmitted sound Analog echo signal
threshold Digital echo signal Integrated
time output signal
threshold
integrator
Time of flight (output)
Blanking time
36
Ultrasonic Sensor
Piezo transducer
  • Frequencies 40 - 180 kHz
  • Sound source piezo/electrostatic transducer
  • transmitter and receiver separated or not
    separated
  • Propagation cone
  • opening angles around 20 to 40 degrees
  • regions of constant depth
  • segments of an arc (sphere for 3D)
  • Typical intensity distribution of an ultrasonic
    sensor

Electrostatic transducer
37
Example
38
Imaging with an US
  • Issues
  • Soft surfaces
  • Sound surfaces that are far from being
    perpendicular to the direction of the sound -gt
    specular reflection

a) 360 scan
b) results from different geometric primitives
39
Characteristics
  • Range 12cm 5 m
  • Accuracy 98-99.1
  • Single sensor operating speed 50Hz
  • 3m -gt 20ms -gt50 measurements per sec
  • Multiple sensors
  • Cycle time-gt0.4sec -gt 2.5Hz-gtlimits speed of
    motion (collisions)

40
Laser Range Sensor
41
Laser Range Sensor Physics
  • Laser
  • Low divergence
  • Well-defined wavelength

42
Time of flight measurement methods
  • Pulsed laser
  • Direct measurement of elapsed time
  • Receiver Picoseconds accuracy
  • Accuracy centimeters
  • Beat frequency between a frequency modulated
    continuous wave and its received reflection
  • Phase shift measurement
  • Technically easier than the above two methods

43
Distance from phase-shift
Target
Reflected beam (r(x))
Amplitude V
Transmitted beam (s(x))
Phase m
Ambiguity! d and d/2 give the same µ
44
Laser Range Sensor
  • Phase-Shift Measurement
  • c speed of light (0.3 m/ns)
  • f the modulating frequency
  • D distance covered by the emitted light
  • for f 5 Mhz (as in the ATT sensor), l 60
    meters

l c/f
45
Laser Range Sensor
  • Confidence in the range (phase estimate) is
    inversely proportional to the square of the
    received signal amplitude.
  • Hence dark, distant objects will not produce such
    good range estimated as closer brighter objects

46
Laser Range Sensor
  • Typical range image of a 2D laser range sensor
    with a rotating mirror. The length of the lines
    through the measurement points indicate the
    uncertainties.

47
Triangulation Ranging
  • Geometry -gt distance
  • Unknown object size project a known light
    pattern onto the environment and use
    triangulation
  • Known object size triangulation without light
    projecting

48
Laser Triangulation (1D)
49
Sharp IR Rangers
50
Conclusions
  • Why how?
  • Sensing Essential to deal with contingencies in
    the world
  • Sensors Make sensing possible
  • Anatomy of sensors
  • Physics, A/D, characteristics
  • Wheel encoders
  • Distance sensors
  • Time of flight
  • Triangulation
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