Design and development of intelligent apartments

106 Pages·2014·2.96 MB·English

by  Author: Zahraa Shahid

Design and development of intelligent
apartments
by
Author: Zahraa Shahid
Advisor: Maurizio Di-Rocco
degree of Master of Arts/Science in Robotics and Intelligent Systems,120 credits
School of Science and Technology
Centre for Applied Autonomous Sensor Systems (AASS)
April 2014
Abstract
Developments in the fields of Ambient Intelligent Environments (AmIE) and Ubiquitous
Computingenvironmentshaveprovidedtheopportunitytodevelopassistivetechnologies
tohelpindividualswhoneedmedicalcareonadailybasis;infacttheintegrationbetween
robots, smart actuators and sensors can ease the execution of several domestic tasks.
Since building a real physical IE is costly, simulations have opened the door to various
possibilities to design, test and explore different scenarios of virtual IE. This thesis
project is aimed at developing an agile prototyping toolkit that provides the means for
users to simulate smart environments for robotics, AmIE and Ubiquitous Computing
fields. Thistoolkitleverageswellknownsoftwaremiddlewares: RobotOperatingSystem
(ROS) and Gazebo. The former is a middleware providing access to several state of the
art techniques used in robotics as well as to a variety of hardware platforms. The latter
provides a simulator which allows to reproduce 3D environments as well as robotic
platforms. Besides reproducing realistic scenarios, the proposed framework easily allows
to go beyond a single apartment: in particular in this thesis a double floor building has
been taken into account. Performances about this scenario and the integration with
existing middlewares are also provided.
Acknowledgements
I would like to thank my supervisor Maurizio Di-Rocco for his guidance and advices
throughout this thesis, and take this opportunity to express my sincere gratitude to my
family for their support and encouragement.
ii
Contents
Abstract i
Acknowledgements ii
List of Figures vi
1 Intoduction, motivation and objectives 1
1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1.1 Motivation for using simulation . . . . . . . . . . . . . . . . . . . . 2
1.2 Desired features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 Related work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.5 Thesis structure: overview of the chapters . . . . . . . . . . . . . . . . . . 8
2 Building intelligent environments 10
2.1 Introduction of simulation platform . . . . . . . . . . . . . . . . . . . . . . 10
2.2 Architecture of Gazebo simulator . . . . . . . . . . . . . . . . . . . . . . . 11
2.2.1 Open dynamics engine (ODE) . . . . . . . . . . . . . . . . . . . . 13
2.2.2 Visualization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Building physical models . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.1 Simulation description format (SDF) . . . . . . . . . . . . . . . . . 14
2.3.2 Links . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.3 Joints and their safety limits . . . . . . . . . . . . . . . . . . . . . 15
2.4 Proportional-Integral-Derivative (PID) controller . . . . . . . . . . . . . . 16
2.5 Interface with a robotic middleware . . . . . . . . . . . . . . . . . . . . . 18
2.5.1 ROS: robot operating system. . . . . . . . . . . . . . . . . . . 18
2.5.2 Plugin interface . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.5.3 Tcp communication or Gazebo communication . . . . . . . 19
2.6 Gazebo-ROS packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3 The developed Angen simulator 20
3.1 System and package overview . . . . . . . . . . . . . . . . . . . . . . . . . 20
3.2 Design of the apartment environment. . . . . . . . . . . . . . . . . . . . . 22
3.2.1 Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.3 Actuators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.3.1 Design of the door model . . . . . . . . . . . . . . . . . . . . . . . 23
iii
Contents iv
3.3.1.1 Implementation of the door model . . . . . . . . . . . . . 24
3.3.1.2 How the simulated door works . . . . . . . . . . . . . . . 26
3.3.2 Design of the elevator model . . . . . . . . . . . . . . . . . . . . . 27
3.3.2.1 Implementation of the elevator model . . . . . . . . . . . 28
3.3.2.2 How the simulated elevator works . . . . . . . . . . . . . 30
3.3.3 Design of the light model . . . . . . . . . . . . . . . . . . . . . . . 31
3.3.3.1 Implementation of the light model . . . . . . . . . . . . . 31
3.3.3.2 How the simulated light works . . . . . . . . . . . . . . . 32
3.4 Turtlebot-Robot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.4.1 Implementation of the Turtlebot-robot . . . . . . . . . . . . . . . . 33
3.4.2 How the simulated Turtlebot robot works . . . . . . . . . . . . . . 34
3.5 Sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.5.1 Camera sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.5.2 Luminosity sensor . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.5.2.1 Design of the simulated luminosity sensor . . . . . . . . 36
3.5.2.2 Implementation of the simulated luminosity sensor . . . 37
3.5.3 Passive infrared sensor (PIR) . . . . . . . . . . . . . . . . . . 39
3.5.3.1 Design of the simulated PIR sensor . . . . . . . . . . . . 40
3.5.3.2 Implementation of the simulated PIR sensor . . . . . . . 42
3.5.4 Optical switch sensor . . . . . . . . . . . . . . . . . . . . . . . . 45
3.5.4.1 Design of the simulated optical switch sensor . . . 45
3.5.4.2 Implementation of the simulated optical switch
sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
3.5.5 Pressure or contact sensor . . . . . . . . . . . . . . . . . . . . 48
3.5.5.1 Design of the simulated contact sensor . . . . . . . . . . . 48
3.5.5.2 Implementation of the simulated contact sensor . . . . . 49
4 Simulation results 52
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.1.1 Angen apartment scenario . . . . . . . . . . . . . . . . . . . . . . . 52
4.2 Components Communication . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.3 Tests of Angen simulator and results . . . . . . . . . . . . . . . . . . . . 57
4.3.1 Performance Results Analysis . . . . . . . . . . . . . . . . . . . . 64
4.3.2 Desired features after the tests . . . . . . . . . . . . . . . . . . . . 66
4.4 Simulation of a robotic task . . . . . . . . . . . . . . . . . . . . . . . . . . 66
5 Discussion and conclusion, limitations and contributions 70
5.1 Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
5.2 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
A Appendix Guide to install ROS and Gazebo simulator 75
A.1 Starting Gazebo simulation: . . . . . . . . . . . . . . . . . . . . . . . . . . 76
A.1.1 Spawn and delete sensors after starting Gazebo: . . . . . . . . . . 77
B Building the simulation environment: 78
B.1 Adding constructed models to model database: . . . . . . . . . . . . . . . 78
Contents v
B.1.1 Create an SDF elevator model . . . . . . . . . . . . . . . . . . . . 78
B.1.2 Create a model of two floors apartment with SDF . . . . . . . . . 79
B.1.3 Create doors with SDF: . . . . . . . . . . . . . . . . . . . . . . . . 80
C Writing actuators’ plug-ins 82
C.0.4 Elevator and lights ROS enabled model plugin . . . . . . . . . . . 82
C.0.5 Elevator controller: . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
C.0.6 Light controller: . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
C.0.7 Door Ros world enabled plugin . . . . . . . . . . . . . . . . . . . . 84
C.0.8 Turtlebot Ros world enabled plugin . . . . . . . . . . . . . . . . . 85
C.1 Launch File.world: . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
D Sensors 87
D.0.1 Contacts sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
D.0.2 Passive Infrared (PIR) sensor: . . . . . . . . . . . . . . . . . . . . . 87
D.0.3 Luminosity sensor: . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
D.0.4 Optical switch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
D.0.5 Camera sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
Bibliography 89
List of Figures
1.1 The constructed inteligent environment is composed by two apartments,
several actuators and sensors . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 Gazebo distributed architecture from top broken into libraries for physics
simulation, rendering, user interface, communication, and sensor gener-
ation. Three different processes will be provided: physics simulation,
sensor generation, gui, and a master for coordination. . . . . . . . . . . . 12
2.2 Two joints of a robot model connecting different parts of rigid bodies. . . 16
2.3 A block diagram of a PID controller in a feedback loop [81] . . . . . . . . 17
3.1 Angen package hierarchy in terms of folders. . . . . . . . . . . . . . . . . . 21
3.2 Door model of the kitchen room when it is opened. . . . . . . . . . . . . . 25
3.3 Door model of the livingroom when it is closed. . . . . . . . . . . . . . . . 26
3.4 Complete PID [83] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.5 PID with P term [83] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.6 Distance with P and I term [83] . . . . . . . . . . . . . . . . . . . . . . . . 29
3.7 Elevator Model with a door on one side and open from the other side. . . 29
3.8 Elevator Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.9 The green rays is a light point rendered in the scene and the light sensor
model is represented with a white geometrical model. . . . . . . . . . . . . 32
3.10 Turtlebot robot is moving in the livingroom. . . . . . . . . . . . . . . . . 33
3.11 The figure describes the communication methodology between ROS and
the actuators. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.12 Acameratypeofsensorembeddedinalightsensormodelwhichislocated
high up in each room to detect the luminance of each wall. . . . . . . . . 38
3.13 PIR sensor in the entrance of the ground floor apartment with its vi-
sualized blue rays in the environment, detecting the motion of dynamic
objects in the environment within 6 m range. . . . . . . . . . . . . . . . . 44
3.14 PIR is moving up and down in the livingroom and posed up in one corner
of the room. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.15 An optical switch model is posed on the top of a door as a laser type of
sensor, represented by two objects distanced at 0.5 m with its visualized
blue rays and its range is cut off when the attached green strip of the
door comes in between the emitter and the detector, detecting the event. 47
3.16 An optical switch model is posed on the top of a door as a laser type
of sensor, represented by two white strips distanced at 0.5 m with its
visualized blue rays and its range is a full ray when the attached green
card of the door is moved away, detecting the door as opened. . . . . . . . 47
vi
List of Figures vii
4.1 This figure depicts how Gazebo organizes the models and plugins to be
placed into Angen world.. . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.2 This figure describes the relationships between developed components in
AngensimulatorandtheproposedmiddlewaresGazeboROSandGazebo
ROR Packages. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55
4.3 CPU% of Added PIRs Objects . . . . . . . . . . . . . . . . . . . . . . . . 60
4.4 CPU% of deploying PIR sensors during Simulation . . . . . . . . . . . . . 60
4.5 CPU% of added Luminosity sensors . . . . . . . . . . . . . . . . . . . . . 62
4.6 CPU% of deploying luminosity sensors objects . . . . . . . . . . . . . . . 62
4.7 CPU% of Added optical switch objects . . . . . . . . . . . . . . . . . . . . 63
4.8 CPU% of deploying optical switch objects . . . . . . . . . . . . . . . . . . 63
4.9 CPU% of Deploying Contact sensors . . . . . . . . . . . . . . . . . . . . . 64
4.10 The Angen world . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.11 The elevator’s door as closed . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.12 The elevator’s door as opened . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.13 This figure describes the PIR sensors performance in terms of its respon-
siveness and the robot’s position in each room is shown along its trajec-
toryinthefirstfloorapartment, showingthedelaybetweeneachdetected
values (red and green points). . . . . . . . . . . . . . . . . . . . . . . . . . 68
4.14 This figure describes the PIR and optical switch sensors performance in
terms of detection and the robot’s position in each room is shown along
its trajectory in the second floor apartment, showing the delay between
each detected values (yellow points). . . . . . . . . . . . . . . . . . . . . . 69
Chapter 1
Intoduction, motivation and
objectives
1.1 Introduction
Ambient Intelligent Environments (AmIE) is a term that was coined by Eli Zelkha,
Brian Epstein and Simon Birrell in 1998 [1]. The first concept, ambient, refers to an en-
vironment with certain requirements such as ubiquitousness[2] and the term Intelligent
Environment (IE) refers to modeling IE via agents should be consistent with modeling
and simulating other entities in the environment [3]. AmIEs’ applications are found in
a number of environments like smart houses, offices and ambient health care [4]. The
other term that is used numerously in the field of intelligent environments in recent
years is Ubiquitous Computing environment and it is necessary to maintain a distinc-
tion between both of the terms. Mark Weiser (1993) has defined Ubiquitous Computing
as computers are scattered around to make use of them throughout the physical envi-
ronment, but also should be effectively invisible to users. On the other hand, Sakamura
(1987) defined the term as information and computing resources that can be attained
by users at any time and anywhere such as smart homes and offices in order to provide
the best services to its habitants [6].
As it can be seen from the definitions of the both terms, AmIE and Ubiquitous Comput-
ing environments are distinct by the former considering the social and human factors,
while the latter is more technology focused and its applications requires advanced proto-
typing[7,8]. Ouraimistodevelopadistributedheterogeneoussystemthatisconsidering
the social and human factor besides the technology. It can be said that the developed
project in this thesis contributes to the AmIE research field. Intelligent Environments
1