start migrasi ke word
parent
207b6d6e3a
commit
251e783c21
|
|
@ -17,17 +17,19 @@ Variable yang dikendalikan pada meteode ini adalah variabel jarak antar agent ya
|
|||
Koordinat yang digunakan tidak mengacu pada koordinat global.
|
||||
Shingga pada penerapannya, formasi berdasarkan jarak menggunakan sensor yang lebih sedikit.
|
||||
Namun salah satu permasalahan pada metode tersebut adalah penerapan model yang lebih nyata.
|
||||
|
||||
Pengembangan formasi berdasarkan jarak telah dikembangkan menggunakan teori \textit{graph}
|
||||
pada single dan double integrator \kutip{Oh2014}
|
||||
dan menerapkannya pada simpel model dengan kendali \textit{Proportional-Integral} \kutip{Rozenheck2015}.
|
||||
Akan tetapi pada penerapan kendali nya,
|
||||
pengukuran jarak antar tetangga diperoleh dari selisih koordinat global robot dan tetangganya.
|
||||
dan telah diterapkannya pada simpel model dengan kendali \textit{Proportional-Integral}(PI) \kutip{Rozenheck2015}.
|
||||
|
||||
Kendali PI pada penelitian sebelumnya tidak dapat langsung diterapkan menggunakan sensor jarak
|
||||
karena kendali tersebut mengambil informasi jarak menggunakan selisih koordinat global kartesian dari setiap robot.
|
||||
Sedangkan dalam praktiknya robot hanya bisa mengukur jarak dan tidak mengetahui koordinat
|
||||
dari robot tetangga.
|
||||
Selain itu, penerapan sensor jarak pada robot memiliki kekurangan untuk mengenali arah gerak
|
||||
robot untuk mencapai jarak yang diinginkan.
|
||||
Sehingga robot diharuskan untuk mengelola koordinat tetangganya.
|
||||
|
||||
Pada penelitian ini akan dikembangkan sebuah algoritma untuk mengetahui koordinat tetangga
|
||||
berdasarkan informasi sensor jarak sehingga hasil pencarian koordinat tersebut dapat
|
||||
digunakan pada kendali formasi berdasarkan jarak.
|
||||
Pada penelitian ini akan dikembangkan sebuah algoritma untuk menemukan koordinat tetangga
|
||||
menggunakan informasi jarak dan digunakan untuk nilai kondisi awal pada kendali formasi berdasarkan jarak.
|
||||
Percobaan akan menggunakan model robot holonomic dengan harapan menjadi langkah awal
|
||||
mengembangkan kendali formasi berdasarkan jarak menggunakan model robot yang lebih nyata.
|
||||
|
|
@ -1,7 +1,7 @@
|
|||
|
||||
\section{Metode}
|
||||
|
||||
\subsection{Kendali Robot Holonomic}
|
||||
\subsection{Model Robot}
|
||||
|
||||
Berikut adalah model dari robot holonomic dalam bentuk \textit{state-space} \kutip{CORREIA20127}.
|
||||
Dimana robot menggunakan tiga buah motor yang dihubungkan pada \textit{omniwheel} sehingga robot
|
||||
|
|
@ -27,6 +27,8 @@ yang diperoleh dari identifikasi secara persamaan fisika.
|
|||
Matrix $K_r \in \mathbb{R}^{3 \times 3}$ adalah parameter \textit{friction} dari robot yang diestimasi dari
|
||||
hasil percobaan.
|
||||
|
||||
\subsection{Kendali Robot Holonomic}
|
||||
|
||||
Kendali dari robot akan menggunakan dua mode \textit{state-feedback}.
|
||||
\textbf{Mode satu}, bertujuan untuk mencapai kecepatan robot yang diinginkan.
|
||||
Untuk mencapai tujuan tersebut akan menggunakan persamaan kendali sebagai berikut
|
||||
|
|
@ -64,7 +66,7 @@ menjadi $y_{c2}(t) = x_{c2}(t) = \begin{bmatrix}
|
|||
A_{c2} = \begin{bmatrix}
|
||||
0 & I \\
|
||||
0 & A_r \\
|
||||
\end{bmatrix} \in \mathbb{R}^{6 \times 6}
|
||||
\end{bmatrix} \in \mathbb{R} ^ {6 \times 6}
|
||||
$,
|
||||
$B_{c2} = \begin{bmatrix}
|
||||
0 \\ B_r
|
||||
|
|
|
|||
|
|
@ -7,5 +7,5 @@
|
|||
% required.
|
||||
|
||||
@Control{biblatex-control,
|
||||
options = {3.7:0:0:1:0:1:1:0:0:0:0:1:3:1:3:1:0:0:3:1:79:+:+:nty},
|
||||
options = {3.7:0:0:1:0:1:1:0:0:0:0:0:3:1:3:1:0:0:3:1:79:+:+:none},
|
||||
}
|
||||
|
|
|
|||
474
article.bbl
474
article.bbl
|
|
@ -16,60 +16,116 @@
|
|||
{}
|
||||
\endgroup
|
||||
|
||||
\datalist[entry]{nty/global//global/global}
|
||||
\entry{CORREIA20127}{article}{}
|
||||
\name{author}{3}{}{%
|
||||
{{hash=CMD}{%
|
||||
family={Correia},
|
||||
familyi={C\bibinitperiod},
|
||||
given={Mariane\bibnamedelima Dourado},
|
||||
giveni={M\bibinitperiod\bibinitdelim D\bibinitperiod},
|
||||
}}%
|
||||
{{hash=GA}{%
|
||||
family={Gustavo},
|
||||
familyi={G\bibinitperiod},
|
||||
given={André},
|
||||
giveni={A\bibinitperiod},
|
||||
}}%
|
||||
{{hash=CS}{%
|
||||
family={Conceição},
|
||||
familyi={C\bibinitperiod},
|
||||
given={Scolari},
|
||||
giveni={S\bibinitperiod},
|
||||
\datalist[entry]{none/global//global/global}
|
||||
\entry{Parker2003}{article}{}
|
||||
\name{author}{1}{}{%
|
||||
{{hash=PL}{%
|
||||
family={Parker},
|
||||
familyi={P\bibinitperiod},
|
||||
given={Lynne},
|
||||
giveni={L\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\keyw{Models, Friction, Parameter estimation, Autonomous mobile robots}
|
||||
\strng{namehash}{CMDGACS1}
|
||||
\strng{fullhash}{CMDGACS1}
|
||||
\strng{namehash}{PL1}
|
||||
\strng{fullhash}{PL1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{C}
|
||||
\field{sortinithash}{C}
|
||||
\field{abstract}{%
|
||||
This paper presents a model of a three-wheeled omnidirectional robot
|
||||
including a static friction model. Besides the modeling is presented a
|
||||
practical approach in order to estimate the coefficients of coulomb and
|
||||
viscous friction, which used sensory information about force and velocity of
|
||||
the robot's center of mass. The proposed model model has the voltages of the
|
||||
motors as inputs and the linear and angular velocities of the robot as
|
||||
outputs. Actual results and simulation with the estimated model are compared
|
||||
to demonstrate the performance of the proposed modeling.%
|
||||
}
|
||||
\verb{doi}
|
||||
\verb https://doi.org/10.3182/20120905-3-HR-2030.00002
|
||||
\verb 10.1007/BF02480877
|
||||
\endverb
|
||||
\field{issn}{1474-6670}
|
||||
\field{note}{10th IFAC Symposium on Robot Control}
|
||||
\field{number}{22}
|
||||
\field{pages}{7 \bibrangedash 12}
|
||||
\field{title}{Modeling of a Three Wheeled Omnidirectional Robot Including
|
||||
Friction Models}
|
||||
\verb{url}
|
||||
\verb http://www.sciencedirect.com/science/article/pii/S1474667016335807
|
||||
\field{pages}{1\bibrangedash 5}
|
||||
\field{title}{Current research in multirobot systems}
|
||||
\field{volume}{7}
|
||||
\field{journaltitle}{Artificial Life and Robotics}
|
||||
\field{month}{03}
|
||||
\field{year}{2003}
|
||||
\endentry
|
||||
|
||||
\entry{Guanghua2013}{inproceedings}{}
|
||||
\name{author}{4}{}{%
|
||||
{{hash=GW}{%
|
||||
family={Guanghua},
|
||||
familyi={G\bibinitperiod},
|
||||
given={Wang},
|
||||
giveni={W\bibinitperiod},
|
||||
}}%
|
||||
{{hash=DL}{%
|
||||
family={Deyi},
|
||||
familyi={D\bibinitperiod},
|
||||
given={Li},
|
||||
giveni={L\bibinitperiod},
|
||||
}}%
|
||||
{{hash=WG}{%
|
||||
family={Wenyan},
|
||||
familyi={W\bibinitperiod},
|
||||
given={Gan},
|
||||
giveni={G\bibinitperiod},
|
||||
}}%
|
||||
{{hash=PJ}{%
|
||||
family={Peng},
|
||||
familyi={P\bibinitperiod},
|
||||
given={Jia},
|
||||
giveni={J\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\strng{namehash}{GW+1}
|
||||
\strng{fullhash}{GWDLWGPJ1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\verb{doi}
|
||||
\verb 10.1109/ISDEA.2012.316
|
||||
\endverb
|
||||
\field{volume}{45}
|
||||
\field{journaltitle}{IFAC Proceedings Volumes}
|
||||
\field{year}{2012}
|
||||
\field{isbn}{978-1-4673-4893-5}
|
||||
\field{pages}{1335\bibrangedash 1339}
|
||||
\field{title}{Study on Formation Control of Multi-Robot Systems}
|
||||
\field{month}{01}
|
||||
\field{year}{2013}
|
||||
\endentry
|
||||
|
||||
\entry{6889491}{inproceedings}{}
|
||||
\name{author}{3}{}{%
|
||||
{{hash=WX}{%
|
||||
family={{Wang}},
|
||||
familyi={W\bibinitperiod},
|
||||
given={X.},
|
||||
giveni={X\bibinitperiod},
|
||||
}}%
|
||||
{{hash=YZ}{%
|
||||
family={{Yan}},
|
||||
familyi={Y\bibinitperiod},
|
||||
given={Z.},
|
||||
giveni={Z\bibinitperiod},
|
||||
}}%
|
||||
{{hash=WJ}{%
|
||||
family={{Wang}},
|
||||
familyi={W\bibinitperiod},
|
||||
given={J.},
|
||||
giveni={J\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\keyw{dynamic programming;mobile robots;multi-robot
|
||||
systems;neurocontrollers;optimal control;predictive control;quadratic
|
||||
programming;recurrent neural nets;torque control;trajectory control;model
|
||||
predictive control approach;multirobot formation control problem;simplified
|
||||
dual neural network;leader-follower scheme;desired trajectory
|
||||
tracking;dynamic quadratic optimization problem;one-layer recurrent neural
|
||||
network;optimal control input;Vectors;Lead;Wheels;Neural networks;Robot
|
||||
kinematics;Mathematical model}
|
||||
\strng{namehash}{WXYZWJ1}
|
||||
\strng{fullhash}{WXYZWJ1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{booktitle}{2014 International Joint Conference on Neural Networks
|
||||
(IJCNN)}
|
||||
\verb{doi}
|
||||
\verb 10.1109/IJCNN.2014.6889491
|
||||
\endverb
|
||||
\field{issn}{2161-4393}
|
||||
\field{pages}{3161\bibrangedash 3166}
|
||||
\field{title}{Model predictive control of multi-robot formation based on
|
||||
the simplified dual neural network}
|
||||
\field{year}{2014}
|
||||
\warn{\item Invalid format of field 'month'}
|
||||
\endentry
|
||||
|
||||
\entry{ELFERIK2016117}{article}{}
|
||||
|
|
@ -98,8 +154,6 @@
|
|||
\strng{fullhash}{FSENMTBU1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{F}
|
||||
\field{sortinithash}{F}
|
||||
\field{abstract}{%
|
||||
Cooperation between autonomous robot vehicles holds several promising
|
||||
advantages like robustness, adaptability, configurability, and scalability.
|
||||
|
|
@ -137,47 +191,102 @@
|
|||
\field{year}{2016}
|
||||
\endentry
|
||||
|
||||
\entry{Guanghua2013}{inproceedings}{}
|
||||
\name{author}{4}{}{%
|
||||
{{hash=GW}{%
|
||||
family={Guanghua},
|
||||
familyi={G\bibinitperiod},
|
||||
given={Wang},
|
||||
giveni={W\bibinitperiod},
|
||||
\entry{YOSHIOKA20085149}{article}{}
|
||||
\name{author}{2}{}{%
|
||||
{{hash=YC}{%
|
||||
family={Yoshioka},
|
||||
familyi={Y\bibinitperiod},
|
||||
given={Chika},
|
||||
giveni={C\bibinitperiod},
|
||||
}}%
|
||||
{{hash=DL}{%
|
||||
family={Deyi},
|
||||
familyi={D\bibinitperiod},
|
||||
given={Li},
|
||||
giveni={L\bibinitperiod},
|
||||
}}%
|
||||
{{hash=WG}{%
|
||||
family={Wenyan},
|
||||
familyi={W\bibinitperiod},
|
||||
given={Gan},
|
||||
giveni={G\bibinitperiod},
|
||||
}}%
|
||||
{{hash=PJ}{%
|
||||
family={Peng},
|
||||
familyi={P\bibinitperiod},
|
||||
given={Jia},
|
||||
giveni={J\bibinitperiod},
|
||||
{{hash=NT}{%
|
||||
family={Namerikawa},
|
||||
familyi={N\bibinitperiod},
|
||||
given={Toru},
|
||||
giveni={T\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\strng{namehash}{GW+1}
|
||||
\strng{fullhash}{GWDLWGPJ1}
|
||||
\strng{namehash}{YCNT1}
|
||||
\strng{fullhash}{YCNT1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{G}
|
||||
\field{sortinithash}{G}
|
||||
\field{abstract}{%
|
||||
This paper deals with formation control strategies based on Virtual
|
||||
Structure (VS) for multi-vehicle systems. We propose several control laws for
|
||||
networked multi-nonholonomic vehicle systems in order to achieve VS
|
||||
consensus, VS Flocking and VS Flocking with collision-avoidance. First,
|
||||
Virtual Vehicle for the feedback linearization is considered, and we propose
|
||||
VS consensus and Flocking control laws based on a virtual structure and
|
||||
consensus algorithms. Then, VS Flocking control law considering collision
|
||||
avoidance is proposed and its asymptotical stability is proven. Finally,
|
||||
simulation and experimental results show effectiveness of our proposed
|
||||
approaches.%
|
||||
}
|
||||
\verb{doi}
|
||||
\verb 10.1109/ISDEA.2012.316
|
||||
\verb https://doi.org/10.3182/20080706-5-KR-1001.00865
|
||||
\endverb
|
||||
\field{isbn}{978-1-4673-4893-5}
|
||||
\field{pages}{1335\bibrangedash 1339}
|
||||
\field{title}{Study on Formation Control of Multi-Robot Systems}
|
||||
\field{month}{01}
|
||||
\field{year}{2013}
|
||||
\field{issn}{1474-6670}
|
||||
\field{note}{17th IFAC World Congress}
|
||||
\field{number}{2}
|
||||
\field{pages}{5149 \bibrangedash 5154}
|
||||
\field{title}{Formation Control of Nonholonomic Multi-Vehicle Systems based
|
||||
on Virtual Structure}
|
||||
\verb{url}
|
||||
\verb http://www.sciencedirect.com/science/article/pii/S1474667016397609
|
||||
\endverb
|
||||
\field{volume}{41}
|
||||
\field{journaltitle}{IFAC Proceedings Volumes}
|
||||
\field{year}{2008}
|
||||
\endentry
|
||||
|
||||
\entry{OH2015424}{article}{}
|
||||
\name{author}{3}{}{%
|
||||
{{hash=OKK}{%
|
||||
family={Oh},
|
||||
familyi={O\bibinitperiod},
|
||||
given={Kwang-Kyo},
|
||||
giveni={K\bibinithyphendelim K\bibinitperiod},
|
||||
}}%
|
||||
{{hash=PMC}{%
|
||||
family={Park},
|
||||
familyi={P\bibinitperiod},
|
||||
given={Myoung-Chul},
|
||||
giveni={M\bibinithyphendelim C\bibinitperiod},
|
||||
}}%
|
||||
{{hash=AHS}{%
|
||||
family={Ahn},
|
||||
familyi={A\bibinitperiod},
|
||||
given={Hyo-Sung},
|
||||
giveni={H\bibinithyphendelim S\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\keyw{Formation control, Position-based control, Displacement-based
|
||||
control, Distance-based control}
|
||||
\strng{namehash}{OKKPMCAHS1}
|
||||
\strng{fullhash}{OKKPMCAHS1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{abstract}{%
|
||||
We present a survey of formation control of multi-agent systems. Focusing
|
||||
on the sensing capability and the interaction topology of agents, we
|
||||
categorize the existing results into position-, displacement-, and
|
||||
distance-based control. We then summarize problem formulations, discuss
|
||||
distinctions, and review recent results of the formation control schemes.
|
||||
Further we review some other results that do not fit into the
|
||||
categorization.%
|
||||
}
|
||||
\verb{doi}
|
||||
\verb https://doi.org/10.1016/j.automatica.2014.10.022
|
||||
\endverb
|
||||
\field{issn}{0005-1098}
|
||||
\field{pages}{424 \bibrangedash 440}
|
||||
\field{title}{A survey of multi-agent formation control}
|
||||
\verb{url}
|
||||
\verb http://www.sciencedirect.com/science/article/pii/S0005109814004038
|
||||
\endverb
|
||||
\field{volume}{53}
|
||||
\field{journaltitle}{Automatica}
|
||||
\field{year}{2015}
|
||||
\endentry
|
||||
|
||||
\entry{Oh2014}{article}{}
|
||||
|
|
@ -201,8 +310,6 @@
|
|||
\strng{fullhash}{OKKAHS1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{O}
|
||||
\field{sortinithash}{O}
|
||||
\field{abstract}{%
|
||||
SUMMARYWe study the local asymptotic stability of undirected formations of
|
||||
single-integrator and double-integrator modeled agents based on interagent
|
||||
|
|
@ -235,84 +342,6 @@
|
|||
\field{year}{2014}
|
||||
\endentry
|
||||
|
||||
\entry{OH2015424}{article}{}
|
||||
\name{author}{3}{}{%
|
||||
{{hash=OKK}{%
|
||||
family={Oh},
|
||||
familyi={O\bibinitperiod},
|
||||
given={Kwang-Kyo},
|
||||
giveni={K\bibinithyphendelim K\bibinitperiod},
|
||||
}}%
|
||||
{{hash=PMC}{%
|
||||
family={Park},
|
||||
familyi={P\bibinitperiod},
|
||||
given={Myoung-Chul},
|
||||
giveni={M\bibinithyphendelim C\bibinitperiod},
|
||||
}}%
|
||||
{{hash=AHS}{%
|
||||
family={Ahn},
|
||||
familyi={A\bibinitperiod},
|
||||
given={Hyo-Sung},
|
||||
giveni={H\bibinithyphendelim S\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\keyw{Formation control, Position-based control, Displacement-based
|
||||
control, Distance-based control}
|
||||
\strng{namehash}{OKKPMCAHS1}
|
||||
\strng{fullhash}{OKKPMCAHS1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{O}
|
||||
\field{sortinithash}{O}
|
||||
\field{abstract}{%
|
||||
We present a survey of formation control of multi-agent systems. Focusing
|
||||
on the sensing capability and the interaction topology of agents, we
|
||||
categorize the existing results into position-, displacement-, and
|
||||
distance-based control. We then summarize problem formulations, discuss
|
||||
distinctions, and review recent results of the formation control schemes.
|
||||
Further we review some other results that do not fit into the
|
||||
categorization.%
|
||||
}
|
||||
\verb{doi}
|
||||
\verb https://doi.org/10.1016/j.automatica.2014.10.022
|
||||
\endverb
|
||||
\field{issn}{0005-1098}
|
||||
\field{pages}{424 \bibrangedash 440}
|
||||
\field{title}{A survey of multi-agent formation control}
|
||||
\verb{url}
|
||||
\verb http://www.sciencedirect.com/science/article/pii/S0005109814004038
|
||||
\endverb
|
||||
\field{volume}{53}
|
||||
\field{journaltitle}{Automatica}
|
||||
\field{year}{2015}
|
||||
\endentry
|
||||
|
||||
\entry{Parker2003}{article}{}
|
||||
\name{author}{1}{}{%
|
||||
{{hash=PL}{%
|
||||
family={Parker},
|
||||
familyi={P\bibinitperiod},
|
||||
given={Lynne},
|
||||
giveni={L\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\strng{namehash}{PL1}
|
||||
\strng{fullhash}{PL1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{P}
|
||||
\field{sortinithash}{P}
|
||||
\verb{doi}
|
||||
\verb 10.1007/BF02480877
|
||||
\endverb
|
||||
\field{pages}{1\bibrangedash 5}
|
||||
\field{title}{Current research in multirobot systems}
|
||||
\field{volume}{7}
|
||||
\field{journaltitle}{Artificial Life and Robotics}
|
||||
\field{month}{03}
|
||||
\field{year}{2003}
|
||||
\endentry
|
||||
|
||||
\entry{Rozenheck2015}{inproceedings}{}
|
||||
\name{author}{3}{}{%
|
||||
{{hash=RO}{%
|
||||
|
|
@ -345,8 +374,6 @@
|
|||
\strng{fullhash}{ROZSZD1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{R}
|
||||
\field{sortinithash}{R}
|
||||
\field{booktitle}{2015 European Control Conference (ECC)}
|
||||
\verb{doi}
|
||||
\verb 10.1109/ECC.2015.7330781
|
||||
|
|
@ -358,102 +385,57 @@
|
|||
\warn{\item Invalid format of field 'month'}
|
||||
\endentry
|
||||
|
||||
\entry{6889491}{inproceedings}{}
|
||||
\entry{CORREIA20127}{article}{}
|
||||
\name{author}{3}{}{%
|
||||
{{hash=WX}{%
|
||||
family={{Wang}},
|
||||
familyi={W\bibinitperiod},
|
||||
given={X.},
|
||||
giveni={X\bibinitperiod},
|
||||
{{hash=CMD}{%
|
||||
family={Correia},
|
||||
familyi={C\bibinitperiod},
|
||||
given={Mariane\bibnamedelima Dourado},
|
||||
giveni={M\bibinitperiod\bibinitdelim D\bibinitperiod},
|
||||
}}%
|
||||
{{hash=YZ}{%
|
||||
family={{Yan}},
|
||||
familyi={Y\bibinitperiod},
|
||||
given={Z.},
|
||||
giveni={Z\bibinitperiod},
|
||||
{{hash=GA}{%
|
||||
family={Gustavo},
|
||||
familyi={G\bibinitperiod},
|
||||
given={André},
|
||||
giveni={A\bibinitperiod},
|
||||
}}%
|
||||
{{hash=WJ}{%
|
||||
family={{Wang}},
|
||||
familyi={W\bibinitperiod},
|
||||
given={J.},
|
||||
giveni={J\bibinitperiod},
|
||||
{{hash=CS}{%
|
||||
family={Conceição},
|
||||
familyi={C\bibinitperiod},
|
||||
given={Scolari},
|
||||
giveni={S\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\keyw{dynamic programming;mobile robots;multi-robot
|
||||
systems;neurocontrollers;optimal control;predictive control;quadratic
|
||||
programming;recurrent neural nets;torque control;trajectory control;model
|
||||
predictive control approach;multirobot formation control problem;simplified
|
||||
dual neural network;leader-follower scheme;desired trajectory
|
||||
tracking;dynamic quadratic optimization problem;one-layer recurrent neural
|
||||
network;optimal control input;Vectors;Lead;Wheels;Neural networks;Robot
|
||||
kinematics;Mathematical model}
|
||||
\strng{namehash}{WXYZWJ1}
|
||||
\strng{fullhash}{WXYZWJ1}
|
||||
\keyw{Models, Friction, Parameter estimation, Autonomous mobile robots}
|
||||
\strng{namehash}{CMDGACS1}
|
||||
\strng{fullhash}{CMDGACS1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{W}
|
||||
\field{sortinithash}{W}
|
||||
\field{booktitle}{2014 International Joint Conference on Neural Networks
|
||||
(IJCNN)}
|
||||
\verb{doi}
|
||||
\verb 10.1109/IJCNN.2014.6889491
|
||||
\endverb
|
||||
\field{issn}{2161-4393}
|
||||
\field{pages}{3161\bibrangedash 3166}
|
||||
\field{title}{Model predictive control of multi-robot formation based on
|
||||
the simplified dual neural network}
|
||||
\field{year}{2014}
|
||||
\warn{\item Invalid format of field 'month'}
|
||||
\endentry
|
||||
|
||||
\entry{YOSHIOKA20085149}{article}{}
|
||||
\name{author}{2}{}{%
|
||||
{{hash=YC}{%
|
||||
family={Yoshioka},
|
||||
familyi={Y\bibinitperiod},
|
||||
given={Chika},
|
||||
giveni={C\bibinitperiod},
|
||||
}}%
|
||||
{{hash=NT}{%
|
||||
family={Namerikawa},
|
||||
familyi={N\bibinitperiod},
|
||||
given={Toru},
|
||||
giveni={T\bibinitperiod},
|
||||
}}%
|
||||
}
|
||||
\strng{namehash}{YCNT1}
|
||||
\strng{fullhash}{YCNT1}
|
||||
\field{labelnamesource}{author}
|
||||
\field{labeltitlesource}{title}
|
||||
\field{sortinit}{Y}
|
||||
\field{sortinithash}{Y}
|
||||
\field{abstract}{%
|
||||
This paper deals with formation control strategies based on Virtual
|
||||
Structure (VS) for multi-vehicle systems. We propose several control laws for
|
||||
networked multi-nonholonomic vehicle systems in order to achieve VS
|
||||
consensus, VS Flocking and VS Flocking with collision-avoidance. First,
|
||||
Virtual Vehicle for the feedback linearization is considered, and we propose
|
||||
VS consensus and Flocking control laws based on a virtual structure and
|
||||
consensus algorithms. Then, VS Flocking control law considering collision
|
||||
avoidance is proposed and its asymptotical stability is proven. Finally,
|
||||
simulation and experimental results show effectiveness of our proposed
|
||||
approaches.%
|
||||
This paper presents a model of a three-wheeled omnidirectional robot
|
||||
including a static friction model. Besides the modeling is presented a
|
||||
practical approach in order to estimate the coefficients of coulomb and
|
||||
viscous friction, which used sensory information about force and velocity of
|
||||
the robot's center of mass. The proposed model model has the voltages of the
|
||||
motors as inputs and the linear and angular velocities of the robot as
|
||||
outputs. Actual results and simulation with the estimated model are compared
|
||||
to demonstrate the performance of the proposed modeling.%
|
||||
}
|
||||
\verb{doi}
|
||||
\verb https://doi.org/10.3182/20080706-5-KR-1001.00865
|
||||
\verb https://doi.org/10.3182/20120905-3-HR-2030.00002
|
||||
\endverb
|
||||
\field{issn}{1474-6670}
|
||||
\field{note}{17th IFAC World Congress}
|
||||
\field{number}{2}
|
||||
\field{pages}{5149 \bibrangedash 5154}
|
||||
\field{title}{Formation Control of Nonholonomic Multi-Vehicle Systems based
|
||||
on Virtual Structure}
|
||||
\field{note}{10th IFAC Symposium on Robot Control}
|
||||
\field{number}{22}
|
||||
\field{pages}{7 \bibrangedash 12}
|
||||
\field{title}{Modeling of a Three Wheeled Omnidirectional Robot Including
|
||||
Friction Models}
|
||||
\verb{url}
|
||||
\verb http://www.sciencedirect.com/science/article/pii/S1474667016397609
|
||||
\verb http://www.sciencedirect.com/science/article/pii/S1474667016335807
|
||||
\endverb
|
||||
\field{volume}{41}
|
||||
\field{volume}{45}
|
||||
\field{journaltitle}{IFAC Proceedings Volumes}
|
||||
\field{year}{2008}
|
||||
\field{year}{2012}
|
||||
\endentry
|
||||
\enddatalist
|
||||
\endinput
|
||||
|
|
|
|||
BIN
article.pdf
BIN
article.pdf
Binary file not shown.
|
|
@ -11,10 +11,10 @@
|
|||
\Var{\Kota} {Malang}
|
||||
|
||||
% Judul laporan.
|
||||
\var{\judul}{Kendali Formasi Berdasarkan Jarak Menggunakan Algoritma Cosinus Pada Mobile Robot}
|
||||
\var{\judul}{Kendali Formasi Mobile Robot Berdasarkan Jarak Menggunakan Algoritma Cosinus}
|
||||
%
|
||||
% Tulis kembali judul laporan, kali ini akan diubah menjadi huruf kapital
|
||||
\Var{\Judul}{Kendali Formasi Berdasarkan Jarak Menggunakan Algoritma Cosinus Pada Mobile Robot}
|
||||
\Var{\Judul}{Kendali Formasi Mobile Robot Berdasarkan Jarak Menggunakan Algoritma Cosinus}
|
||||
%
|
||||
% Tulis kembali judul laporan namun dengan bahasa Ingris
|
||||
\var{\judulInggris}{Formation Control Distance-Based Using Cosinus Algoritm For Multi Mobile-Robot}
|
||||
|
|
|
|||
|
|
@ -220,7 +220,7 @@
|
|||
%
|
||||
\@ifclassloaded{article}
|
||||
{
|
||||
\usepackage[backend=bibtex,autocite=inline]{biblatex}
|
||||
\usepackage[backend=bibtex,autocite=inline,sorting=none]{biblatex}
|
||||
}
|
||||
{
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue