Field and Service Robotics

Odometry sensors

Navigation (internal) Sensors

To sense robot’s own stateMagnetic compass (absolute heading)Gyro (angular speed => change of heading)Acceleration sensors (acceleration)tako, encoder (speed, distance)syncro, resolver (speed, position)

Dead-reckoningMaritime term from deduced reckoning”Murtoviivasuunnistus” in FinnishThe position is calculated on the basis of previousposition, heading and travelled distanceNo external beacons neededVery sensitive to the heading measurement!Error is accumulating all the time!!With ”basic sensors” a very low cost alternativedo always!High accuracy costs a lot!

Dead-reckoningThe distance is measured with odometry– easy with wheels and tracks– difficult with legs and in maritime and airborne applications

The heading can be defined by using:– Measurements and vehicle kinematics

steering angle + odometry measurement (ackermann)Odometry (skid steering)

– Direct measurementcompass gyroetc.

Kinematics

cot cotΘ Θidl

− =0cot cotΘ Θsa idl

= +2

Ackerman Steering

Differential Steering (J2B2)

D D Dl r=+2 = the total distance

Θ =−D Dd

l r = heading

Note: Dynamics (mass inertia) affects always, especially when speed increases!

Note: different angles!Alpha = steering angleTheta = body angle

Here:theta = stering angle

”No” Kinematics

Tracked and wheeled skid-steered vehiclesWheels have to slide sideways, while turningSurface properties and CoG ”say the last word” during the steering process

Error accumulation

Distance error from slippery etc. incrementally moves the calculated final positionHeading error from steering, gyro, etc. has much bigger effect

heading is critical!!

Odometers

tachometer (DC motor)potentiometersynchroresolveroptical encodermagnetic encoderinductive encoderkapasitive encoder

The most used odometers are:optical encodersresolverspotentiometers

Potentiometerlow-cost, easy to useresistace/voltage proportional to the absolute angle/positionnot for continuous rotation, mechanical wearing, nonlinear in accurate measurements

DC-Tachometer

Like normal DC-motor (DC with brushes, AC without)Output voltage proportional to the rotation speedcheap, output also in low speedswearing brushes (not in brushless), analog output

Synchro

Electro mechanical system which transfers the angle information with high accuracythe receiver rotor will follow the transmitter rotor when same alternating voltage is supplied to both rotors

ResolverSpecial configuration of synchroThe output phase is proportional to shaft absoluteangle and output (amplitude)/frequency is proportional to the shaft speed (ideal feedback sensor for brushless DC-motors)

Variable reluctance resolverRotor consists of only electro-magnetic steel sheetsOne-phase of exciting coil and two-phase output coils are wound on the stator coreThe contour of rotor is made as ellipsoid i.e. air-gap between the stator and rotor is varied in sinusoid depending on the shaft angleNo brushes or slipringsExtremely robustBoth speed and absolute angleoutputUsed in Toyota Prius

http://www.scribd.com/doc/38612704/Tamagawa

Resolver

ReliableAccurateDual outputAnaloghigh price(brushes wear)

Brushless resolvers arealso availablebiggerno mechanical wearingbigger power consuption

Variable reluctanceresolvers are the future

Optical Encoders

accurateenduringlow-price (incremental)usually not as robust as resolvers

Incremental Optical EncoderPrimary quantity is relative distance/angle (pulse)The most simple is one channel takometer Adding an other channel also the direction of rotation can be sensed

Absolute Encoder

Measures the absolute position/angleMore expensive than incremental oneBest for slow rotations with high accuracy

Absolute Encoder

The most used configurations are:A: Gray-code B: Binary code

Ground Speed RadarThe wheels and tracks always slide => odemetry is not accurateDoppler radar gives the real groung speed, proportional to the speed difference between the radar and the target

Sensor Fusion

Usually there is several (unaccurate) positioning measurements available like odometry, steering angle, gyro, (D)GPS, acceleration sensors etc.To get the best possible estimate of the position the sensor data has to be fusedKalman-filter is the most used estimation algorithm in robotics