Learning Robot Interactive Behaviors in Presence of Humans and Groups of Humans

135 Pages·2017·5.45 MB·English

Learning Robot Interactive Behaviors in Presence of
Humans and Groups of Humans
Omar A Islas Ramírez
To cite this version:
Omar A Islas Ramírez. Learning Robot Interactive Behaviors in Presence of Humans and Groups of
Humans. Artificial Intelligence [cs.AI]. Université Pierre et Marie Curie - Paris VI, 2016. English.
￿NNT: 2016PA066632￿. ￿tel-01652202￿
HAL Id: tel-01652202
https://theses.hal.science/tel-01652202
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Universite´ Pierre et Marie Curie
Doctoral Dissertation
Learning Robot Interactive Behaviors in
Presence of Humans and Groups of
Humans
Omar Adair Islas Ram´ırez
supervised by
Raja Chatila, Research Director and Professor, Universit´e Pierre et Marie Curie
Mohamed Chetouani, Professor, Universit´e Pierre et Marie Curie
Reviewers
Anne Spalanzani, Associate Professor, Universit´e de Grenoble
Mouaddib Abdel-Illah, Professor, UNICAEN
Examiners
Rachid Alami, Research Director, LAAS-CNRS
Jacques Malenfant, Professor, Universit´e Pierre et Marie Curie
To be presented on 28/11/2016

“Dedicado a mis padres y hermanos”
To my parents and brothers
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Abstract
Inthepastyears,robotshavebeenapartofoureverydaylives. Evenwhenwedonotseethem,
we depend on them to build our computers, mobile phones, cars and more. They are also been
usedfororganizingstocksinwarehouses. And,withthegrowthofautonomouscars,weseethem
driving autonomously on highways and cities.
Another area of growth is social robotics. We can see a lot of studies such as robots helping
children with autism. Other robots are being used to receive people in hotels or to interact
with people in shopping centers. In the latter examples, robots need to understand people
behavior. Inaddition,inthecaseofmobilerobots,theyneedtoknowhowtonavigateinhuman
environments.
In the context of human environments, this thesis explores socially acceptable navigation of
robotstowardspeople. Togiveanexample,whenarobotapproachesoneperson,therobotshall
by no means treat people as an obstacle because the robot get really close to the human and
interfere with her personal space. The human is an entity that needs to be considered based on
social norms that we (humans) use on a daily basis.
In a first time, we explore how a robot can approach one person. A person is an entity that
can be bothered if someone or something approaches invading her personal space. The person
also will feel distressed when she is approached from behind. These social norms have to be
respected by the robot. For this reason, we decided to model the behavior of the robot through
learning algorithms. We manually approach a robot to a person several times and the robot
learns how to reproduce this behavior.
In a second time, we present how a robot can understand what is a group of people. We,
humans, have the ability to do this intuitively. However, for a robot, a mathematical model is
essential. Lastly, we address how a robot can approach a group of people. We use exemplary
demonstrations to teach this behavior to the robot. We evaluate then the robot’s movements by
for example, observing if the robot invades people’s personal space during the trajectory.
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Acknowledgment and Dedications
I am thankful to my advisors, Raja Chatila and Mohamed Chetouani, who guided me tirelessly
throuhoutmyPhD.TheyarebothbrilliantresearchersandIwasfortunatetoworkwithbothof
them and benefit from both their perspectives. They provided the input and the means needed
to develop and finish my research.
This work is the result of collaboration with other people. Harmish Khambhaita and Rachid
Alami provided several discussions and also technical knowledge and help to develop Chapter 3.
Giovanna Varni and Mihai Andries provided deep insights and help to formulate the contents of
Chapter 4.
Beyond direct collaborations, many other people contributed to my graduate work. Discus-
sions about research and life with Zhanat Kappasov. A dear group of friends formed within the
ISIRlab,namelyCarlosVina,ArthurBouton,AnisNajar,HananSalam,AlexandradosSantos,
Ryan Lobber, Carlos Maestre, Alex Vasquez, Ninon Candalh-Touta and some others.
Iwouldalsoliketothanktomyfriendsbeyondtheuniversitycampus. Theyprovidedmewith
thedistractionenoughtoliveahealthylife. Byplayingvolleyball,watchingmovies,hangingout
ortraveling. ThankstoGustavoMendoza,JuliaPenick,Katie,LaureTezier,SebastianHurtado,
Sebastian Montana, Marion Girod, as well as my late friend Ida Pili.
I would like to deeply thank my companion Blerina Hahxi for supporting me during an
important period of my PhD. I love the way we are together and the way you cherish me.
Lastly,IwanttothankmyfamilyforsupportingmenotonlyduringmyPhD,butthroughout
every step in my life. You are my rock and my inspiration.
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Contents
Abstract iii
Acknowledgment and Dedications v
Table of Contents vii
List of Figures xi
List of Tables xix
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Summary of Contributions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Outline of the Dissertation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Related Works 5
2.1 Identification of Groups of People . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.1 Static Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.1.2 Dynamic Groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2.2 Social Navigation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2.1 Navigating within Humans and Motion Planners . . . . . . . . . . . . . . 12
2.2.2 Approaching Humans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.3 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
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