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CS 491/691(X) - Lecture 5 1
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Topics: Introduction toRobotics
CS 491/691(X)Lecture 5
Instructor: Monica Nicolescu
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CS 491/691(X) - Lecture 5 4
Reflective OptosensorsInclude a source of light emitter (lightemitting diodes LED) and a lightdetector (photodiode or phototransistor)
Two arrangements, depending on thepositions of the emitter and detector Reflectance sensors: Emitter and detector
are side by side; Light reflects from the objectback into the detector
Break-beam sensors: The emitter anddetector face each other; Object is detected if light between them is interrupted
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CS 491/691(X) - Lecture 5 5
CalibrationAmbient / background light can interfere with the sensor measurement
The ambient light level should be subtracted to get only theemitter light level
Calibration : the process of adjusting a mechanism so as tomaximize its performance
Ambient light can change sensors need to be calibratedrepeatedly
Detecting ambient light is difficult if the emitter has the samewavelength
Adjust the wavelength of the emitter
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CS 491/691(X) - Lecture 5 6
Infra Red (IR) LightIR light works at a frequency different than ambientlight
IR sensors are used in the same ways as the visible
light sensors, but more robustly Reflectance sensors, break beams
Sensor reports the amount of overall illumination, ambient lighting and the light from light source
More powerful way to use infrared sensing Modulation/demodulation : rapidly turn on and off the source
of light
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CS 491/691(X) - Lecture 5 7
Modulation/DemodulationModulated IR is commonly
used for communication
Modulationis done by flashing the light source at aparticular frequency
This signal is detected by a demodulator tuned to
that particular frequencyOffers great insensitivity to ambient light Flashes of light can be detected even if weak
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CS 491/691(X) - Lecture 5 8
Infrared CommunicationBit frames All bits take the same amount of
time to transmit
Sample the signal in the middle of the bit frame
Used for standard computer/modem communication Useful when the waveform can be reliably transmitted
Bit intervals
Sampled at the falling edge
Duration of interval between sampling determines whether it is a0 or 1
Common in commercial use
Useful when it is difficult to control the exact shape of the
waveform
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CS 491/691(X) - Lecture 5 9
Proximity SensingIdeal application for modulated/demodulatedIR light sensing
Light from the emitter is reflected back intodetector by a nearby object, indicating
whether an object is present LED emitter and detector are pointed in the
same direction
Modulated light is far less susceptible to
environmental variables amount of ambient light and the reflectivity of
different objects
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CS 491/691(X) - Lecture 5 10
Break Beam SensorsAny pair of compatible emitter-detector devicescan be used to make a break-beam sensor
Examples:
Incadescent flashlight bulb and photocell
Red LEDs and visible-light-sensitive photo-transistors
IR emitters and detectors
Where have you seen these?
Break beams and clever burglars in movies
In robotics they are mostly used for keeping trackof shaft rotation
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CS 491/691(X) - Lecture 5 11
Shaft Encoding
Shaft encoders Measure the angular rotation of a shaft or an axle
Provide position and velocity information about the
shaftSpeedometers: measure how fast the wheels areturning
Odometers: measure the number of rotations of thewheels
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CS 491/691(X) - Lecture 5 12
Measuring RotationA perforated disk is mounted on the shaft
An emitterdetector pair is placed on both
sides of the disk
As the shaft rotates, the holes in the diskinterrupt the light beam
These light pulses are counted thus monitoring the rotation of the
shaft
The more notches, the higher the resolution of the encoder
One notch, only complete rotations can be counted
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CS 491/691(X) - Lecture 5 13
General Encoder Properties
Encoders are active sensors
Produce and measure a wave
function of light intensityThe wave peaks are counted to compute the speed
of the shaft
Encoders measure rotational velocity and position
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CS 491/691(X) - Lecture 5 14
Color-Based Encoders
Use a reflectance sensors to count the rotationsPaint the disk wedges in alternating contrastingcolors
Black wedges absorb light, white reflect it and onlyreflections are counted
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CS 491/691(X) - Lecture 5 15
Uses of Encoders
Velocity can be measured at a driven (active) wheel
at a passive wheel (e.g., dragged behind a legged robot)
By combining position and velocity information, onecan: move in a straight line
rotate by a fixed angle
Can be difficult due to wheel and gear slippage andto backlash in geartrains
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CS 491/691(X) - Lecture 5 16
Q uadrature Shaft EncodingHow can we measure direction of rotation?
Idea: Use two encoders instead of one
Align sensors to be 90 degrees out of phase
Compare the outputs of both sensors at eachtime step with the previous time step
Only one sensor changes state (on/off) at eachtime step, based on the direction of the shaftrotation this determines the direction of
rotation A counter is incremented in the encoder that
was on
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CS 491/691(X) - Lecture 5 17
Which Direction is the Shaft Moving?
Encoder A = 1 and Encoder B = 0
If moving to position AB=00,the position count is
incremented If moving to the position
AB=11, the position count isdecremented
State transition table:
Previous state = current stateno change in position
Single-bit changeincrementing / decrementing thecount
Double-bit change illegaltransition
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CS 491/691(X) - Lecture 5 18
Uses of Q SE in RoboticsRobot arms with complex joints e.g., rotary/ball joints like knees or
shoulders
Cartesian robots, overhead cranes
The rotation of a long worm screwmoves an arm/rack back and fortalong an axis
Copy machines, printers
ElevatorsMotion of robot wheels
Dead-reckoning positioning
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Ultrasonic Distance SensingS onars: so(und) na(vigation) r (anging)Based on the time-of-flight principleThe emitter sends a chirp of sound
If the sound encounters a barrier it reflects back tothe sensor
The reflection is detected by a receiver circuit,tuned to the frequency of the emitter D istance to objects can be computed by measuringthe elapsed time between the chirp and the echoSound travels about 0.89 milliseconds per foot
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CS 491/691(X) - Lecture 5 20
Sonar SensorsE mitter is a membrane that transforms mechanicalenergy into a ping (inaudible sound wave)
The receiver is a microphone tuned to thefrequency of the emitted sound
Polaroid Ultrasound Sensor Used in a camera to measure the
distance from the camera to the subject
for auto-focus system Emits in a 30 degree sound cone
Has a range of 32 feet
Operates at 50 KHz
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EcholocationE cholocation = finding location based on sonar Numerous animals use echolocation
Bats use sound for:
finding pray, avoid obstacles, find mates,communication with other bats
Dolphins/Whales:find small fish, swim through mazes
Natural sensors are much more complex thanartificial ones
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Specular Reflection
Sound does not reflect directly and come right backSpecular reflection The sound wave bounces off multiple sources before
returning to the detector
Smoothness The smoother the surface the more likely is that the sound
would bounce off
Incident angle The smaller the incident angle of the sound wave the
higher the probability that the sound will bounce off
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CS 491/691(X) - Lecture 5 23
Improving Accuracy
Use rough surfaces in lab environments
Multiple sensors covering the same area
Multiple readings over time to detect discontinuities
Active sensing
In spite of these problems sonars are used
successfully in robotics applications Navigation
Mapping
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CS 491/691(X) - Lecture 5 24
Laser Sensing
High accuracy sensor Lasers use light time-of-flightLight is emitted in a beam (3mm) rather than a cone
Provide higher resolution
For small distances light travels faster than it can bemeasured use phase-shift measurement
SICK LMS200
360 readings over an 180-degrees, 10HzDisadvantages: cost, weight, power, price
mostly 2D
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CS 491/691(X) - Lecture 5 25
Visual Sensing
Cameras try to model biological eyesMachine visionis a highly difficult research area Reconstruction
What is that? Who is that? Where is that?Robotics requires answers related to achievinggoals Not usually necessary to reconstruct the entire world
Applications Security, robotics (mapping, navigation)
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CS 491/691(X) - Lecture 5 26
Principles of Cameras
Camerashave many similarities with the human eye The light goes through an opening ( iris - lens) and hits the
image plane (retina ) The retina is attached to light-sensitive elements ( rods,
cones silicon circuits ) Only objects at a particular range are
in focus ( fovea ) depth of field 512x512 pixels ( cameras ),120x10 6 rods and 6x10 6 cones ( eye )
The brightness is proportional to the
amount of light reflected from the objects
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CS 491/691(X) - Lecture 5 27
Image Brightness
Brightness depends on reflectance of the surface patch
position and distribution of the light sourcesin the environment
amount of light reflected from other objectsin the scene onto the surface patch
Two types of reflection Specular (smooth surfaces)
Diffuse (rough sourfaces)
Necessary to account for theseproperties for correct objectreconstruction complex computation
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CS 491/691(X) - Lecture 5 28
Early VisionThe retina is attached to numerous rods and cones which, inturn, are attached to nerve cells (neurons )The nerves process the information; they perform "earlyvision", and pass information on throughout the brain to do
"higher-level" vision processingThe typical first step ("early vision") is edge detection, i.e., findall the edges in the image
Suppose we have a b&w camera with a 512 x 512 pixel image
Each pixel has an intensity level between white and black
How do we find an object in the image? Do we know ifthere is one?
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CS 491/691(X) - Lecture 5 29
Edge Detection
Edge= a curve in the image across whichthere is a change in brightnessFinding edges Differentiate the image and look for areas
where the magnitude of the derivative is largeDifficulties Not only edges produce changes in brightness:
shadows, noise
Smoothing Filter the image using convolution Use filters of various orientations
Segmentation: get objects out of the lines
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Model-Based Vision
Compare the current image with images of similar objects(models ) stored in memory
Models provide prior information about the objects
Storing models
Line drawings
Several views of the same object
Repeatable features (two eyes, a nose, a mouth)
Difficulties
Translation, orientation and scale
Not known what is the object in the image
Occlusion
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CS 491/691(X) - Lecture 5 31
Vision from Motion
Take advantage of motion to facilitate visionStatic system can detect moving objects Subtract two consecutive images from each other the
movement between frames
Moving system can detect static objects At consecutive time steps continuous objects move as one
Exact movement of the camera should be known
Robots are typically moving themselves Need to consider the movement of the robot
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Stereo Vision
3D information can becomputed from two
images
Compute relativepositions of cameras
Compute disparity
displacement of a point in3D between the two images
Disparity is inverse proportional with actual distancein 3D
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CS 491/691(X) - Lecture 5 33
Biological Vision
Similar visual strategies are used in natureModel-based vision is essential for object/people
recognition
Vestibular occular reflex Eyes stay fixed while the head/body is moving to stabilize
the image
Stereo vision Typical in carnivores
Human vision is particularly good at recognizingshadows, textures, contours, other shapes
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Vision for Robots
If complete scene reconstruction is not needed wecan simplify the problem based on the taskrequirements
Use colorUse a combination of color and movementUse small images
Combine other sensors with visionUse knowledge about the environment
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Examples of Vision-Based Navigation
Running QRIO Sony Aibo obstacle avoidance
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Readings
F. Martin: Chapter 6
M. Matari : 9