Sensors CSCI545 Introduction to Robotics Hadi Moradi Previous - - PDF document

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Sensors CSCI545 Introduction to Robotics Hadi Moradi Previous - - PDF document

Sensors CSCI545 Introduction to Robotics Hadi Moradi Previous Lecture DC motors DC motors Inefficient Operating voltage Operating current Stall current Stall torque Stall torque Gearing up and down Gear


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Sensors

CSCI545 Introduction to Robotics Hadi Moradi

Previous Lecture

DC motors DC motors

Inefficient Operating voltage Operating current Stall current Stall torque Stall torque Gearing up and down Gear ratios PWM Servo motors vs. stepper motors

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Sensors

Perception through sensors Perception through sensors

Contact: bump, switch Distance: Ultrasound, radar, infra red Light level: photo cells, cameras Sound level: microphone

Sensors

Perception through sensors

Perception through sensors

Strain: strain gauge Rotation: encoders Magnetism: compasses Smell: chemical

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Sensors

Perception through sensors Perception through sensors

Temperature: thermal, infra red Inclination: inclinometers, gyroscopes

Pressure: pressure gauges

Pressure: pressure gauges Altitude: altimeters …

Sensors

Simple complex

Simple

complex

Contact switch

human retina

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The General Question

Given the sensory reading what was the

Given the sensory reading what was the

world like?

Example: Skin Example: Skin

Levels of Processing

A switch:

  • pen = 0 volts

Closed = 5 volts

A digital scale:

Microphone:

Microphone: Camera:

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Proprioception

Sensing information Sensing information

Proprioception: Exteroception:

Examples of proprioception

Sensor Fusion

Combining multiple sensors

Combining multiple sensors Difficulties:

E l H b i

Example: Human brain

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Magnetic Field Sensor of Baby Loggerhead Sea Turtles

  • Field Inclination Angle
  • Field Intensity
  • Neuron sensors in the brain?

http://news.nationalgeographic.com/news/ 2001/10/1012_TVanimalnavigation.html

http://faculty.washington.edu /chudler/magtur.html

Magnetic Field Sensor of Baby Loggerhead Sea Turtles

http://www.unc.edu/depts/oceanweb/turtles/ Research by Dr. Kenneth Lohmann

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Ohm’s Law

V= IR

V= IR

V = voltage

(volts)

I = current

(Amps)

R = resistance

(Ohms)

Switch Sensors

Open vs closed

Open vs. closed

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Light Sensors

A variable resistor

A variable resistor

that changes based

  • n the light.

Brighter light = > low resistance low resistance darker light = > Higher resistance

The Importance of shielding

Note: Shielding, position, and

directionality of the photocells are important.

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Resistive Position Sensors

Originally

Originally

developed for video game control.

Bend Sensor

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Potentiometers

Volume control in your stereo

Volume control in your stereo Typically called pots

Example

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Example Reflective Opto-sensors

Emitter and detector

Emitter and detector Emitter:

LED

Detector:

Photodiode Photodiode Phototransistor

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Photodiode vs. Photoresistor

Photoresistor:

Photoresistor: Photodiode/phototransistor:

Phototransistor vs. Photodiode:

Applications

  • bject presence detection
  • bject presence detection
  • bject distance detection

surface feature detection

(finding/following markers/tape)

wall/boundary tracking wall/boundary tracking rotational shaft encoding

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Sensor limitations

Light reflectivity:

g y

Surface color Texture

Ambient light: How to overcome the ambient light? Sensor calibration

= > Partially observable

Break Beam Sensors

  • Any pair of compatible emitter-

detector devices can be used to make a break-beam sensor

  • Examples:
  • Where have you seen these?
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Shaft Encoding

Measure angular rotation Measure angular rotation Example:

Speedometer: speed of rotation

p p

Odometer: number of rotations

Q: What happens if there is only one

notch in the disk?

An Example

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Quadrature Shaft Encoder

Clockwise rotation signal

Output Signal

ccw cw

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Modulation and Demodulation

  • f Light

Problem: Ambient light Problem: Ambient light Solution: Example: Home remote control Usage:

g

Modulation and Demodulation

  • f Light
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Proximity Sensing

The distance to a nearby object The distance to a nearby object

Just the return of signal

Distance Sensing

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Infra Red (IR) Sensors

Infra red part of the spectrum

Infra red part of the spectrum Used like break beam and reflectance

sensors

Advantage

Time of Flight

Emitter: send a

Emitter: send a

chirp

Collector:

Receives the bounce back

Elapsed time

1.12 feet/ms

Called

echolocation

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Bats Man Made Example

Used to map

Used to map

undersea surface

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Undersea Mapping Picture from Bluefin Robotics

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Problem 1: Multiple Reflections

Which reflection

Which reflection

gets back earlier?

Which reflection

should be used for calculation?

Object 2 Object 1 Sonar

Problem 2: Specular Reflection

Graze the surface

Graze the surface

and bounce off

Object 2 Object 1 Sonar

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Problems Other Usages: NavBelt

http://www.engin.umich.edu/research/mrl/00MoRob_19.html

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Navchair

http://www.engin.umich.edu/research/mrl/00MoRob_19.html

GuideCane

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GuideCane Machine Vision Machine Vision

Problem: determine the objects in the Problem: determine the objects in the

environment (Understand the environment).

Example: RoboCup

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The Physics of Vision The Physics of Vision

Light goes through the iris Impinges retina

Camera Light Processing Camera Light Processing

A very simple processing: convert the image to a normal image

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Image Reconstruction Image Reconstruction

Reconstruction: what was the world like Reconstruction: what was the world like

that produced this image?

  • Pixelizing the Image Plane

Pixelizing the Image Plane

pixels: picture cells

pixels: picture cells

Each picture divided into small cells

Typical camera: 512 X 512 pixels Human eye:

120 x 10^ 6 rods

120 x 10^ 6 rods 6 x 10^ 6 cones

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Image Brightness Image Brightness

B i h i l h f

Brightness: proportional to the amount of

light directed toward the camera

Brightness depends on:

  • Patch Brightness

Patch Brightness

Th b i h d d

The brightness depends on:

specular (bounce off the surface) diffuse (re-emitted)

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First Steps of Early Vision First Steps of Early Vision

Example: Example:

b&w camera

512 x 512 pixel image plane.

intensity level between white and black

Question:

Do we know if there is an object?

Do we know if there is an object? How do we find an object in the image?

An Example An Example

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Edge Detection Edge Detection

Edges: curves in the image plane with

significant change in the brightness level

A simple approach: to look for sharp

brightness changes:

Problem:

Example: Human Body Project Example: Human Body Project

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Smoothing of Noise Smoothing of Noise

Noise: Small picks in differentiated image Noise: Small picks in differentiated image. Eliminating noise:

  • Finding Objects

Finding Objects

Step 2: Find objects among all those edges

Step 2: Find objects among all those edges. Segmentation:

Q ti

Questions:

How do we know which lines correspond to

which objects,

What makes an object?

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Finding Objects Finding Objects

Use clues to detect Use clues to detect

  • bjects. The math is

hard...

Clues for Segmentation (1) Clues for Segmentation (1)

Use stored models (model-based vision) Use stored models (model based vision)

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Clues for Segmentation (1) Clues for Segmentation (1)

  • MAKRO 1.1 drives to a T-shaped

junction, measures its width, drives back, performs a turn, stops, drives back and performs a turn back into the main pipe. Second run, different point of view

Clues for Segmentation(2) Clues for Segmentation(2)

Use motion (motion vision) Use motion (motion vision)

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Clues for Segmentation(3) Clues for Segmentation(3)

Use binocular stereopsis

Use binocular stereopsis

(stereo vision)

  • Clues for Segmentation(4)

Clues for Segmentation(4)

Left image Right image

Image after disparity

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Clues for Segmentation(5) Clues for Segmentation(5)

Use texture

Use texture Use shading

shading, contours,

Use shading

shading, contours, …

recover shape in a similar way as from texture

Complexity of Vision Sensing Complexity of Vision Sensing

Reconstruction:

Reconstruction: If no need for reconstruction:

Si lif i i i

Simplify vision processing

Q: What are some ways of doing that?

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Simplifying Vision Simplifying Vision

  • Use color

Use a smaller image plane (e.g., a line) Use other sensors to complement vision Use other sensors to complement vision Use task-specific information

Question: Determine the object in this image

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Structured Light Vision Structured Light Vision

Project a light on a Project a light on a

mirror and scan the area.

You may avoid

rotating motor and scan with a full scan with a full surface.

Images courtesy of http://www.caligari.com/

Structured Light Vision Structured Light Vision

Any object in the Any object in the

environment cuts the light.

Images courtesy of http://www.caligari.com/

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Structured Light Vision Structured Light Vision

A) The whole scene, B) The object w/o laser light, C) the difference

Images courtesy of http://www.caligari.com/

Structured Light Vision Structured Light Vision

  • Y= projection of the
  • Y= projection of the

laser on the image plane

  • H= height of the

camera

  • Question: How do

you calculate r?

Images courtesy of http://www.caligari.com/