Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita...
Transcript of Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita...
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
Roland Siegwart, Margarita Chli, Nick Lawrance
2021 | Perception I - add ons │Sensors 1
Perception I │SensorsAutonomous Mobile Robots
Spring 2021
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
raw data
“position“global map
Sensing Acting
InformationExtraction
PathExecution
CognitionPath Planning
Real WorldEnvironment
LocalizationMap Building
Mot
ion
Con
trol
Perc
eptio
n
actuatorcommands
environment modellocal map path
Mobile Robot Control Schemeknowledge,data base
missioncommands
see-think-act
2021 | Perception I - add ons │Sensors 2
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
32021 | Perception I - add ons │Sensors
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
“In AI, the easy problems are hard, and the hard problems are easy” S. Pinker. The Language Instinct. New York: Harper Perennial Modern Classics, 1994
2021 | Perception I - add ons │Sensors 4
Perception is hard!
beating the world’s chess master: EASY
create a machine with some“common sense”: very HARD
see-think-act
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
5
Perception | definition
Raw DataVision, Laser, Sound, Smell, …
FeaturesCorners, Lines, Colors, Phonemes, …
ObjectsDoors, Humans, Coke bottle, car , …
Places / SituationsA specific room, a meeting situation, …
•Models / Semantics• imposed• learned
•Models• imposed• learned
Navigation
Interaction
Servicing / Reasoning•Functional / Contextual Relationships of Objects
• imposed• learned• spatial / temporal/semantic
Ext
ract
ing
Info
rmat
ion
2021 | Perception I - add ons │Sensors
Understanding
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
Tactile sensors or bumpers Detection of physical contact, security switches
GPS Global localization and navigation
Inertial Measurement Unit (IMU) Orientation and acceleration of the robot
Wheel encoders Local motion estimation (odometry)
Laser scanners Obstacle avoidance, motion estimation, scene
interpretation (road detection, pedestrians)
Cameras Texture information, motion estimation, scene
interpretation6
Sensors | common sensors and their use in mobile robotics
GPS
Inertial measurement unit
Wheel encoders
Laser scanner
Omnidirectional camera
Standard camera
Laser scanners
Security switch
2021 | Perception I - add ons │Sensors
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
Use cases measure position or speed of the wheels or steering integrate wheel movements to get an estimate of the position → odometry
optical encoders are proprioceptive sensors typical resolutions: 64 - 2048 increments per revolution. for high resolution: interpolation
Working principle of optical encoders regular: counts the number of transitions but cannot tell the
direction of motion quadrature: uses four sensors in quadrature-phase shift. The
ordering of which wave produces a rising edge first tells the direction of motion. Additionally, resolution is 4 times bigger
a single slot in the outer track generates one reference pulse per revolution
2021 | Perception I - add ons │Sensors 7
Wheel / Motor Encoders
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
2. Main Characteristics • The four fields on the scanning reticle are shifted
in phase relative to each other by one quarter of the grating period, which equals 360°/(number of lines)
• This configuration allows the detection of a change in direction
• Easy to interface with a micro-controller
2021 | Perception I - add ons │Sensors 8
Wheel / Motor Encoders
scanning reticle fields
scale slits
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
2021 | Perception I - add ons │Sensors 9
Wheel / Motor Encoders
Notice what happens when the direction changes:
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
2021 | Perception I - add ons │Sensors 10
Ultrasonic Range Sensor (time of flight, sound)1. Operational PrincipleAn ultrasonic pulse is generated by a piezo-electric emitter, reflected by an object in its path, and sensed by a piezo-electric receiver. Based on the speed of sound in air and the elapsed time from emission to reception, the distance between the sensor and the object is easily calculated.
2. Main Characteristics• Precision influenced by angle to object (as
illustrated on the next slide)• Useful in ranges from several cm to several
meters• Typically relatively inexpensive
3. Applications• Distance measurement (also for transparent
surfaces)• Collision detection
emitter
receiver
2tvd
<http://www.robot-electronics.co.uk/shop/Ultrasonic_Rangers1999.htm>
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
not directive – opening cone
soft surfaces that absorb most of the sound energy
surfaces that are fare from being perpendicular to the direction of the sound specular reflections
Low update frequency (speed of sound)
2021 | Perception I - add ons │Sensors 11
Ultrasonic Range Sensor | Limitations
a) 360° scan b) results from different geometric primitives
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
2021 | Perception I - add ons │Sensors 12
Laser-based 3D mapping | scan matching
scan t1
scan t2
scan matching
Mapping & Localization
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
Roland Siegwart, Margarita Chli, Nick Lawrance
2021 | Perception I │Spotlight on GPS 13
Perception I │Spotlight on GPSAutonomous Mobile Robots
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
Working Principle Location of any GPS receiver is determined through a time-of-flight measurement between
the satellites and user. The satellites send their orbital location (ephemeris) plus time; the receiver computes its
location through trilateration and time correction.
Technical challenges: Time synchronization between the individual satellites and the GPS receiver Real time update of the exact location of the satellites Precise measurement of the time-of-flight Interferences with other signals
Depending on the constellation, today an accuracy belowone meter in global positioning can be reached.
14
Global Positioning System (GPS)
2021 | Perception I │Spotlight on GPS
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
2021 | Perception I │Spotlight on GPS 15
Global Positioning System (GPS)
Time synchronization: ultra-precision time synchronization is very important atomic clocks on each satellite monitoring them from different ground stations.
Electromagnetic radiation travels roughly 0.3 m per nanosecond (speed of light) position accuracy proportional to precision of time measurement
Real-time update of the exact location of the satellites: monitoring the satellites from several widely distributed ground stations master station analyses all the measurements and transmits the actual position to each of the satellites
Exact measurement of the time of flight quartz clock on the GPS receivers are not very precise the range measurement with four satellite allows to identify the three values (x, y, z) for the position
and the clock correction ΔT Commercial GPS receivers have nominal position accuracy of around 3 meters
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
2021 | Perception I │Spotlight on GPS 16
Global Positioning System (GPS) | interference with local environment
Satellite coverage Multipath problem
|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance
ASLAutonomous Systems Lab
Standard GPS Ephemeris (satellite position) errors: 1 meter Tropospheric delays: 1 meter Unmodeled ionosphere delays: 10 meters Multipath: 0.5 - 100 meters Number of satellites under line of sight
RTK (Real-Time Kinematic) - GPS Additional measurements of the phase of the
signal's carrier wave reference station or interpolated virtual station to
provide real-time corrections→ providing up to centimeter-level accuracy
17
GPS error sources
2021 | Perception I │Spotlight on GPS