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ROBOTICS
01PEEQW
Basilio Bona
DAUIN – Politecnico di Torino
Mobile & Service Robotics
Sensors for Robotics – 1
Onboard sensors
Basilio Bona
ROBOTICS 01PEEQW - 2015/2016
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Onboard sensors
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Onboard sensors
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Definitions
A sensor is a device that produces a measurable response to a
change in a physical quantity related to the robot or the
environment
Usually, sensors convert the physical quantity into a signal which
can be measured electrically
The sensors are classified according to the following criteria:
1. Primary Input quantity (aka measurand)
2. Measured property (as temperature, flow, displacement,
proximity, acceleration, etc.)
3. Transduction principles
4. Material and technology
5. Application
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Sensors types
Proprioceptive sensors (PC)
They measure quantities coming from the robot itself, e.g.,
motor speed, wheel loads, robot heading, battery charge
status, etc.
Exteroceptive sensors (EC)
They measure quantities coming from the environment: e.g.,
walls distance, earth magnetic fields, intensity of the
ambient light, obstacle positions, etc.
Passive sensors (SP)
They use the energy coming from the environment
Active sensors (SA)
They use the energy they produce and measure the reaction
of the environment (better performance, but may influence
the environment)
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Sensors types
Analog Sensors: they measure continuous variables and provide the
information as a physical reading (mercury thermometers and old
style voltmeters are good examples of analog sensors)
Digital Sensors: they measure continuous or discrete variables, but
the provided information is always digital, i.e., discretized
Continuous Sensors: although the name is somehow misleading,
continuous sensors (analog or digital) provide a reading that is on a
continuous range, as opposite to ON/OFF sensors
Binary Sensors : they give only two levels of information ON/OFF or
YES/NO: a lamp that switches on when a certain temperature level is
attained, is an analog binary sensor
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Sensors classification
Category
Tactile sensors/proximity
sensors
Active wheel sensors
Heading sensors with respect to
a fixed RF
Sensors
Type
Contact sensors (on/off), bumpers
EC - SP
Proximity sensors
(inductive/capacitive)
EC - SA
Distance sensors
(inductive/capacitive)
EC - SA
Potentiometric encoders
PC - SP
Optical, magnetic, Hall-effect,
inductive, capacitive encoders,
syncro and resolvers
PC - SA
Compasses
EC - SP
Gyroscopes
PC - SP
Inclinometers
Absolute cartesian sensors
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EC – SP/A
GPS (outdoor only)
EC – SA
Optical or RF beacons
EC – SA
Ultrasonic beacons
EC – SA
Reflective beacons
EC – SA
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Sensors classification
Category
Active distance sensors
(active ranging)
Motion and velocity sensors
(speed relative to fixed or
mobile objects)
Vision sensors: distance from
stereo vision, feature analysis,
segmentation, object
recognition
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Sensors
Type
Reflective sensors
EC - SA
Ultrasonic sensors
EC - SA
Laser range finders, Laser scanners
EC - SA
Optical triangulation (1D)
EC - SA
Structured light (2D)
EC - SA
Doppler radar
EC - SA
Doppler sound
EC - SA
CCD and CMOS cameras
EC - SA
Integrated packages for visual
ranging
EC - SA
Integrated packages for object
tracking
EC - SA
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Sensor characteristics
Dynamic range
Resolution
Linearity
Bandwidth or frequency
Transfer function
Reproducibility/precision
Accuracy
Systematic errors
Hysteresis
Temperature coefficient
Noise and disturbances: signal/noise ratio
Cost
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Sensor characteristics
Dynamic range
Ratio between lower and upper measurement limits, expressed in
dB
Example: voltage sensor min=1 mV, max 20V: dynamic range 86dB
Range = upper limit of dynamic range
Resolution
Minimum measurable difference between two values
Resolution = lower limit of dynamic range
Digital sensors: it depends on the bit number of the A/D converter
Example 8 bit=255 range 20 V -> 20/255 = 0.08
Bandwidth
Difference between upper and lower frequencies
Large bandwidth means large transfer rate
Lower bandwidth is possible in acceleration sensors
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Accuracy and precision
accuracy
True value
Measurement
precision
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Accuracy and Precision
Precision = Repeatability = Reproducibility
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Precise but
not accurate
Accurate but
not precise
Not accurate and
not precise
Precise and
accurate
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Noise
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Noise
All sensors are subject to noise
Due to random fluctuations or electromagnetic interference, an
undesired component is added to the measured signal that
cannot be precisely known
If the noise is smaller than the measurement fluctuations and the
noise introduced by the electronic components, it is not influent
If not, it can degrade the entire chain plant-sensor-controller and
make it unusable
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Noise
Noise is often spread on a large frequency spectrum and many
noise sources produce the so-called white noise, where the
power spectral density is equal at every frequency
The noise is often characterized by the spectral density of the
noise Root Mean Square (RMS), given as
V / Hz
Since it is a density, to obtain the RMS value one shall integrate
the spectrum density in the frequency band of interest. This type
of distribution adds to the measure an error term that is
proportional to the square root of the bandwidth of the
measuring system
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White noise
White noise is a random signal (or process) with a flat power
spectral density
The signal contains equal power within a fixed bandwidth at any
center frequency
An infinite-bandwidth white noise signal is a purely theoretical
construction
The bandwidth of white noise is limited in practice by the
mechanism of noise generation, by the transmission medium and
by finite observation capabilities
A random signal is considered “white noise” if it is observed to
have a flat spectrum over the widest possible bandwidth
White noise is often used for modeling purposes
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Noise types
Noise are of many types:
Shot noise
Thermal noise
Flicker noise
Burst noise
Avalanche noise
To know the noise type is important for modeling purposes
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Shot noise
Shot noise, often called quantum noise, is always associated to
random fluctuations of the electric current in electrical
conductors, due to the current being carried by discrete charges
(electrons) whose number per unit time fluctuates randomly
This is often an issue in p-n junctions. In metal wires this is much
less important, since correlation between individual electrons
remove these random fluctuations
Shot noise is distinct from current fluctuations in thermal
equilibrium, which happen without any applied voltage and
without any average current flowing. These thermal equilibrium
current fluctuations are known as thermal noise
The shot noise spectrum is flat
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Thermal noise
Thermal noise, also called Johnson–Nyquist noise, is the
electronic noise generated by the thermal agitation of the
charge carriers (usually the electrons) inside an electrical
conductor at equilibrium, which happens regardless of any
applied voltage
Thermal noise is approximately white
With good approximation the amplitude of the signal has a
Gaussian probability density function
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Flicker noise
Flicker noise, also called 1/f noise or pink noise is characterized
by a frequency spectrum such that the power spectral density is
inversely proportional to the frequency
It is always present in active components of electronic circuits
and in many passive ones
It is proportional to the current amplitude, so if the current is
sufficiently low, the thermal noise will predominate
example of pink noise spectrum
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