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| Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli, Nick Lawrance 2021 | Perception I - add ons Sensors 1 Perception I Sensors Autonomous Mobile Robots Spring 2021

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Page 1: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 2: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 3: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|Autonomous Mobile RobotsRoland Siegwart, Margarita Chli, Nick Lawrance

ASLAutonomous Systems Lab

32021 | Perception I - add ons │Sensors

Page 4: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 5: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 6: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 7: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 8: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 9: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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:

Page 10: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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>

Page 11: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 12: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 13: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

Page 14: Perception I Sensors Autonomous Mobile Robots...Autonomous Mobile Robots Roland Siegwart, Margarita Chli, Nick Lawrance ASL Autonomous Systems Lab Roland Siegwart, Margarita Chli,

|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

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|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

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|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

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|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