ROBOTICS ROBOTICS 01PEEQW 01PEEQW 01PEEQW 01PEEQW Basilio Bona Basilio Bona DAUIN DAUIN – – Politecnico di Torino Politecnico di Torino
Mobile & Service Robotics Mobile & Service Robotics Sensors for Sensors for Robotics Robotics – – 1 1
An Example of robots with their sensors Basilio Bona 3 ROBOTICS 01PEEQW
Another example Omnivision Camera (360 ° ) Pan-Tilt-Zoom (PTZ) camera IMU=Inertial Measurement Unit Sonars Laser Scanner Encoders inside differential wheels Bumpers Passive support wheel Basilio Bona 4 ROBOTICS 01PEEQW
Definition � A sensor is a device that produces a measurable response to a change in a physical condition (such as temperature) or to a change in a chemical concentration � Usually commonly used sensors convert the physical quantity into a signal which can be measured electrically � The sensors are classified according to the following � The sensors are classified according to the following criteria: 1. Primary Input quantity (aka measurand) 2. Transduction principles 3. Measured property (as temperature, flow, displacement, proximity, acceleration, etc.) 4. Material and technology 5. Application Basilio Bona 5 ROBOTICS 01PEEQW
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 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) Basilio Bona 6 ROBOTICS 01PEEQW
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 Basilio Bona 7 ROBOTICS 01PEEQW
Sensors classification Category Sensors Type Contact sensors (on/off), bumpers EC - SP Proximity sensors Tactile sensors/proximity EC - SA (inductive/capacitive) sensors Distance sensors EC - SA (inductive/capacitive) Potentiometric encoders PC - SP Optical, magnetic, Hall-effect, Active wheel sensors inductive, capacitive encoders, inductive, capacitive encoders, PC - SA PC - SA syncro and resolvers Compasses EC - SP Heading sensors with respect to Gyroscopes PC - SP a fixed RF Inclinometers EC – SP/A GPS (outdoor only) EC – SA Optical or RF beacons EC – SA Absolute cartesian sensors Ultrasonic beacons EC – SA Refelctive beacons EC – SA Basilio Bona 8 ROBOTICS 01PEEQW
Sensors classification Category Sensors Type Reflective sensors EC - SA Ultrasonic sensors EC - SA Active distance sensors Laser range finders, Laser scanners EC - SA (active ranging) Optical triangulation (1D) EC - SA Structured light (2D) EC - SA Motion and velocity sensors Motion and velocity sensors Doppler radar Doppler radar EC - SA EC - SA (speed relative to fixed or Doppler sound EC - SA mobile objects) CCD and CMOS cameras EC - SA Vision sensors: distance from Integrated packages for visual EC - SA stereo vision, feature analysis, ranging segmentation, object recognition Integrated packages for object EC - SA tracking Basilio Bona 9 ROBOTICS 01PEEQW
Sensor characteristics � Dynamic range � Resolution � Linearity � Bandwidth or frequency � Transfer function � Reproducibility/precision � Reproducibility/precision � Accuracy � Systematic errors � Hysteresis � Temperature coefficient � Noise and disturbances: signal/noise ratio � Cost Basilio Bona 10 ROBOTICS 01PEEQW
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 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=25510 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 Basilio Bona 11 ROBOTICS 01PEEQW
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Accuracy and precision Basilio Bona 13 ROBOTICS 01PEEQW
Accuracy and Precision Precision = Repeatability = Reproducibility Accurate but Precise but not precise not accurate Not accurate and Precise and not precise accurate Basilio Bona 14 ROBOTICS 01PEEQW
Noise Noise Noise Noise 15 ROBOTICS 01PEEQW
Noise � All sensors are subject to noise, since, due to random fluctuations or electromagnetic interference, they add to the measured signal an undesired component 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 is not influent � On the contrary it can degrade the entire chain plant- sensor-controller and make it unusable Basilio Bona 16 ROBOTICS 01PEEQW
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 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 Basilio Bona 17 ROBOTICS 01PEEQW
Noise types � Noise are of many types; these include � Shot noise � Thermal noise � Flicker noise � Burst noise � Avalanche noise � Avalanche noise � To know the noise type is important for modeling purposes Basilio Bona 18 ROBOTICS 01PEEQW
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 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 Basilio Bona 19 ROBOTICS 01PEEQW
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 � Thermal noise is approximately white � With good approximation the amplitude of the signal has a Gaussian probability density function Basilio Bona 20 ROBOTICS 01PEEQW
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 is sufficiently low, the thermal noise will predominate Basilio Bona 21 ROBOTICS 01PEEQW
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 Basilio Bona 22 ROBOTICS 01PEEQW
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