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+*.synctex.gz
+*.bbl
+*.blg
+.DS_Store
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+*.bcf
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-# Deep modeling with hybrid petri nets
+# Deep modeling for self-reproducing robots
+> This is a paper about how to use deep modeling to describe a self-reproducing robots control system
 
+[ShareLaTex link](https://tex.zih.tu-dresden.de/7733911278qxxqdzbkcnzf
+) 
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+\documentclass{article}
+
+\usepackage[utf8]{inputenc}
+
+\usepackage[english]{babel}
+\usepackage{biblatex}
+\addbibresource{mine.bib}
+\usepackage{graphicx}
+\graphicspath{{./figures/}}
+\usepackage{listings}
+\usepackage{float}
+
+\title{A deep domain-specific model framework for self-reproducing robots control system}
+\author{Wanqi Zhao}
+\date{\today}
+
+\begin{document}
+\maketitle
+
+\begin{abstract}
+As robots play more and more important roles in diverse and complex scenarios in the real world, especially in remote cases, monomorphic robots can just be applied for duplicated and manageable tasks, and more research turn to compose multiple robots automatically to achieve more robust, flexible and scalable systems. In this paper, we propose a deep domain-specific model framework for the multi-robot system to escort reliable co-working tasks of diverse robots. We introduce the assemble and reconstruct proceed with a series of robots that are self-control and communicable to provide individual control modules and constraints between separate layers.
+\end{abstract}
+
+% \begin{keyword}
+% Deep Model; Domain-specific languages; Multi-robot control system;
+% \end{keyword}
+
+\section{Introduction}
+In modern software engineering, the application of a disciplined and robust system development is a big challenge. Much research consecrates to cope with the challenges of turning abstract requirements into concrete programs regularly. As current platforms and languages have limitations, especially in robotics, the diversity of hardware, demand, and agents increase the toughness of reuse codes in substantive development.  Model-driven software engineering (MDSE) has been proven as a reliable method to solve several vexing problems in software development, such as the integration of large-scale and platform-independent systems, embedded control systems and real-time systems development. 
+
+For worldwide robotics software development research, one of the central deficiencies is the lack of architectural design that can afford the increasing, strict and even partially conflicting variegated requirements. More concretely, the request of robotic software systems are \cite{Frigerio1} \cite{Schlegel}:
+\begin{itemize}
+    \item Flexible and dependable control: often robotic systems have multiple and context-dependent goals, it requires the control system should have the ability to regulate robots' state, trajectory track and task process, etc. And the control system should be robust to adapt to the changes in conditioned sensors and components. 
+    \item Real-time ability: some components of the program must have the capability to execute and update in real-time like network topology, robot status, mapping, task planning, force control loop, etc.
+    \item Generation and integration of components: most robotic systems are developed for the specific domains(technical application domains) and the separation of appropriate components has a positive impact on recurring developments. The generation and integration of components include hardware parts(the virtual components for plug-in/plug-out sensors, joysticks, control modules, etc.) and software parts(navigation, localization, obstacles detection, mapping, etc.) is desired.
+    \item Debug and safety of systems: generally the components of robotic systems are independent, distributed and abstract, this improves the difficulties of debugging especially to evaluate the constraints and relationships between components. Debugging is an important request for building a high-level robust software system. As more co-working scenarios of humans and robots, the safety problem should be valued as well.
+    \item Constraints and context of the environment: as more and more utilization scenarios in robotic systems, robotic applications are not limited to unique and indoor environments and the research of robotics should face and meet the requirements of more real-world scenes like aviation, deep sea, etc. 
+\end{itemize}
+For self-replicating robots, except the requirements we mentioned before, the system should also have abilities to solve logic in task assignments, status updates of robots during moving, multi-robot coordination, and discrete or continuous communication, etc. In this paper, we discuss how to use model-driven software engineering (MDSE) to assemble, disassemble, reconstruct and control robot modules in the self-replicating system. Section 2 describes the definition and improvement of self-reproducing robots and the challenges we face. Section 3 describes the deep model and domain specific language(DSL) theory in robotics, which is the foundation of architecture in this paper. Section 4 describes the detail design of the system. Section 5 introduces some related research and what we will do in the future.
+
+\section{Self-reproducing robots}
+The concept of self-reproducing can be tracked over 60 years ago that was proposed by John von Neumann \cite{Schwartz1967TheoryOS} and he presented a theoretical perspective of automata theory in self-reproducing machines. He donated the logical design of self-reproducing cellular automaton that provides connection between natural organisms and computers. With more manufacture design to achieve self-reproducing robots such as \cite{Chirikjian2002}\cite{Jorgensen2005}\cite{Tuci2006} and automatic algorithms for navigation and transmutation such as \cite{Kaloutsakis2011}\cite{Suthakorn2003}, self-reproducing robots are not just generalization and utopian thoughts. Software is vital nexus in task assignments \cite{Gerkey2004}, distributed locomotion \cite{Butler2003}, genetic generation \cite{Menezes2012}, and multi-robot coordination transformation \cite{Yan2013}. Because of the booming of other areas such as new materials \cite{Polygerinos2015ModelingOS} and 3D printing \cite{Ellery2016}, self-reproducing robots have more organizations. The integration, constraints, and hierarchies of diverse code modules become an issue that is worth considering in software engineering structure. 
+
+In \cite{Suthakorn2003-1} they divided self-reproducing robots into two primary categories: \textit{Directly reproducing} and \textit{Indirectly reproducing} robots. Directly reproducing means the robots can produce a replica of itself in one generation. For directly reproducing, each robot should have one or several basic abilities such as communication, mobility, and electricity and so on or depend on external passive fixtures. Indirectly reproducing means several automatic work cells that are composed of several independent robots or a group of co-working robots to manufacture replicas of robots. 
+
+For modeling these two categories of self-reproducing robots, we define modules in groups:
+\begin{itemize}
+    \item Master robots: An entirely functional robot that can reproduce itself or other types of robots by assembling robot modules.
+    \item Robot modules: A set of robot modules equipped to master robots to compose and reproduce themselves. These modules can include different resources such as sensors, emitter, and actuators or can be solid objects.
+    \item Environments:A world model that can describe the confinement of working robots. The world model can provide additional information for the whole system.
+    \item Robot work cells: in indirectly reproducing, robot work cells conclude one or more original robots to assist processes of producing and constructing.
+\end{itemize}
+    
+% In \cite{Chirikjian2002TowardSR}
+
+
+% In \cite{Gerkey2004} they proposed three axes describe the multi-task robots: \textit{Multi-robot tasks mean robots can execute several tasks simultaneously}, \textit{Multi-robot tasks mean various tasks need various robots}, \textit{Multi-robot tasks should consider Instantaneous assignment and Time-extended assignment}.
+
+
+% \cite{Jones} concluded three design considerations of heterogeneous robots:
+% \begin{enumerate}
+%     \item 
+% \end{enumerate}
+
+
+
+
+
+
+\section{Deep domain-specific model in robotics}
+
+Deep modeling is fundamentally originated for deep instantiation between hierarchies and domains of meta-models which has outside-hierarchy linguistic and ontological classifications. We usually use domain-specific language as abstract models to focus on behavioral concepts. These behavioral concepts have context and constraints with different layers. Deep modeling is based on these scenarios which can help us to separate concerns in case to pollute elements in the exact domain with fixed-level models. A deep model employs the notion called clabject which can be classes and objects at the same time. For multi-level modeling, elements need to have both inherent type and instance facet. To clear the instantiation of multi-levels in deep modeling, each clabject has a positive integer denominated "potency" to present how many following levels a clabject can be instantiated.
+% how to use this in robotics
+
+When it comes to robotic programming, for example, the concept of a robot described by codes should include types of robots like humanoid robots, mobile robots or robot arms, components of robots like wheels, legs or arms, references to other classes like sensors.  Figure \ref{fig:robot_model} shows a universal robotic system model,  there are three fundamental models we should consider to design a robotic system: \textit{Robot Model} includes static and dynamic properties of robots. The \textit{Robot Model} not only describes the compose of robots but also the transformation during the progress; The \textit{Environment Model} should consider all external constraints and accessorial information; The \textit{Control Model} represents the behavior robots can have with the limits of circumstances and features. Considering the reusability, extendibility, modularization concepts of DSMLs (Domain-Specific Modelling Languages), we should define generic methods instead of individual models as much as possible, but not to contaminate the elements, for example, all mobile robots have "move" function, but not all of them can "avoid obstacles" and components to be used in "move" action can be "legs" or "wheels". 
+
+\begin{figure}[h]
+    \centering
+    \includegraphics[width=\textwidth]{figures/Robot_model_new.png}
+    \caption{Universal robotic system model}
+    \label{fig:robot_model}
+\end{figure}
+
+With model build in \cite{Atkinson2014}, they defined \emph{Robot Modelling Language Types}, \emph{Robot Modelling Language},
+ \emph{Robot Behavior Model} and \emph{Behavior Enactment Model} levels between linguistic Meta-model 
+ and real-world to instantiate a robotic entity in deep modeling. For the specific robot and task, 
+ it is easy to build a static model without taking the task sequences and execution time into account. Self-reproducing robots are endowed with more comprehensive missions. We will expand the model to represent the self-reproducing robots system in section 4.
+
+
+
+\section{Deep model design for self-reproducing robots}
+Figure \ref{fig:deep_model} shows an illustration of the traditional three linguistic levels in orthogonal classification architecture (OCA) \cite{Atkinson2009AFI}, which is composed of three linguistic classification levels, L2 - L0. From left to right, the L2 level is the linguistic metamodel that defines the abstract syntax of the model structure. The middle column, level L1 illustrates the ontological domain models that can achieve deep instantiation by the concept of \textit{potency}. The L0 level represents the entities and concepts in the real world. The domain-specific modeling language in the middle level is to provide concrete syntax of clabjects at Robot System Modeling Language Types, which standardize the textual definition of the framework. Further, it specifies other domain models, such as the semantics to describe models in \textit{Robot System Modeling Language}, the features to model robots in \textit{Robot Modeling}, the self-reproducing progresses in \textit{Process Modeling}, and state transition in \textit{Specific State Modeling}.
+
+% whole architecture of design
+\begin{figure}[H]
+    \centering
+    \includegraphics[height=9cm,width=\textwidth]{figures/Deep_Model_Design.png}
+    \caption{An overview of the deep model modelling framework for self-reproducing robots}
+    \label{fig:deep_model}
+\end{figure}
+
+\subsection{Robot System Modeling Language Types}
+The Robot System Modeling Language Types (RSMLT) model is the fundamental epitome of the whole self-reproducing robotic system model concept.  It comprises not only the entities in the model like robots and components but also precise processes and states.  These types are the foundation of the robotic programming language that gives a full range of robotic models. We propose seven types in RSMLT: RobotSystemType, ProcessType, BehaviorType, StateType, ComponentType, RobotType, EnvironmentType as we show in Figure \ref{fig:RobotTypes}. 
+
+\begin{figure}[H]
+    \centering
+    \includegraphics[scale=0.5]{figures/RobotSystemType.png}
+    \caption{Robot System Modeling Language Types}
+    \label{fig:RobotTypes}
+\end{figure}
+
+\begin{itemize}
+    \item RobotSystemType:
+\end{itemize}
+
+\subsection{Robot System Modeling Language}
+The Robot System Modeling Language is to instantiate a cluster of robot models that compose the robot system, initial the environment for the robot system, including the information and criterion, stipulate hierarchies of robots with processes. 
+\subsection{Robot Modeling}
+Robot Modeling is an explicit model of robots that instantiated from the last Robot System Modeling level. Robot Modeling defines features of robots that serve a series of actions in robotic system control. 
+\subsection{Process Modeling}
+Process modeling encompasses a set of established behaviors of multiple robots that are defined in the last Robot Modeling level. During self-reproducing workflows, robots should "follow the steps" or "make decisions" when they face various scenarios and Robot Modeling boundary what kind of actions robots can execute. Further, Process Modeling can support the robot system to choose suitable robots to run appropriate activities. 
+\subsection{Specific State Modeling}
+The hierarchies and synchronizing in the robotic control system is the main subject that should be considered in programming. Finite state machines can ensure the functioning of operations by a limited number of states and outputs on state transitions after receiving inputs \cite{Lee1996PrinciplesAM}. Thus, we define state modeling to guarantee the reliability of processed propagation. 
+
+
+\section{Related work}
+% In \cite{Frigerio} they defined a DSL to calculate the transformation in robotic system.
+\section{Conclusion and Future work}
+After the theory of self-reproducing robots emerged, more and more research about hardware and manufacturing applications have been proposed and achieved. However, most study weakens the role of software architecture plays in robotic control systems.  It is essential to model robotic programming for reuse and integration of robot components considering the constraints and context of the environment.  In this paper, we have presented a deep-domain specific model framework to provide an efficient, extensive, and flexible prototype for support of general utilization. Furthermore, it builds comprehensive models and concrete syntaxes to characterize the single-robot and multi-robot systems. In the future, we will implement more synthesized models to assist the whole formation better, such as algorithms behind processes, state transition, and system optimization. 
+
+
+\printbibliography
+
+
+\end{document}
\ No newline at end of file
diff --git a/mine.bib b/mine.bib
new file mode 100644
index 0000000000000000000000000000000000000000..a4a16ee0a19784158c104bc237fa9d2172b7329c
--- /dev/null
+++ b/mine.bib
@@ -0,0 +1,257 @@
+@techreport{Schlegel,
+author = {Schlegel, Christian and Steck, Andreas and Lotz, Alex},
+file = {:Users/zhaowanqi/Library/Application Support/Mendeley Desktop/Downloaded/Schlegel, Steck, Lotz - Unknown - Robotic Software Systems From Code-Driven to Model-Driven Software Development.pdf:pdf},
+mendeley-groups = {Robots/DSL,Role model based domain-specific modeling framework for mutli-robot applications},
+title = {{Robotic Software Systems: From Code-Driven to Model-Driven Software Development}},
+url = {www.intechopen.com}
+}
+
+@techreport{Frigerio1,
+abstract = {Rigid body dynamics algorithms play a crucial role in several components of a robot controller and simulations. Real time constraints in high frequency control loops and time requirements of specific applications demand these functions to be very efficient. Despite the availability of established algorithms , their efficient implementation for a specific robot still is a tedious and error-prone task. However, these components are simply necessary to get high performance controllers. To achieve efficient yet well maintainable implementations of dynamics algorithms we propose to use a domain specific language to describe the kinematics/dynamics model of a robot. Since the algorithms are parameterized on this model, executable code tailored for a specific robot can be generated, thanks to the facilities available for DSLs. This approach allows the users to deal only with the high level description of their robot and relieves them from problematic hand-crafted development; resources and efforts can then be focused on open research questions. Preliminary results about the generation of efficient code for inverse dynamics will be presented as a proof of concept of this approach.},
+archivePrefix = {arXiv},
+arxivId = {1301.7190v1},
+author = {Frigerio, Marco and Buchli, Jonas and Caldwell, Darwin G},
+eprint = {1301.7190v1},
+file = {:Users/zhaowanqi/Library/Application Support/Mendeley Desktop/Downloaded/Frigerio, Buchli, Caldwell - Unknown - A Domain Specific Language for kinematic models and fast implementations of robot dynamics algori.pdf:pdf},
+mendeley-groups = {Robots/Model,Robots/DSL,Role model based domain-specific modeling framework for mutli-robot applications},
+title = {{A Domain Specific Language for kinematic models and fast implementations of robot dynamics algorithms}}
+}
+@inproceedings{Schwartz1967TheoryOS,
+  title={Theory of Self-Reproducing Automata},
+  author={Jacob T. Schwartz and John von Neumann and Arthur W. Burks},
+  year={1967}
+}
+@inproceedings{Chirikjian2002TowardSR,
+  title={Toward Self-replicating Robots},
+  author={Gregory S. Chirikjian and Jackrit Suthakorn},
+  booktitle={ISER},
+  year={2002}
+}
+@inproceedings{Atkinson2014,
+abstract = {In the future, robots will play an increasingly important role in many areas of human society from domestic housekeeping and geriatric care to manufacturing and running businesses. To best exploit these new opportunities, and allow third party developers to create new robot applications in as simple and efficient a manner as possible, new user-friendly approaches for describing desired robot behavior need to be supported. This paper introduces a prototype domain-specific modeling framework designed to support the quick, simple and reliable creation of control software for standard robot platforms. To provide the best mix of general purpose and domain-specific language features the framework leverages the deep modeling paradigm and accommodates the execution phases as well as design phases of a robot application's lifecycle.},
+author = {Atkinson, Colin and Gerbig, Ralph and Markert, Katharina and Zrianina, Mariia and Egurnov, Alexander and Kajzar, Fabian},
+booktitle = {CEUR Workshop Proceedings},
+file = {:home/qiqi/Documents/papers/Atkinson et al. - 2014 - Towards a deep, domain-specific modeling framework for robot applications.pdf:pdf},
+issn = {16130073},
+keywords = {Deep modeling,Domain-specific languages,Linguistic classification,Ontological classification},
+mendeley-groups = {General Model,Robots/Model,Robots/Role model based domain-specific modeling framework for mutli-robot applications},
+pages = {4--15},
+title = {{Towards a deep, domain-specific modeling framework for robot applications}},
+volume = {1319},
+year = {2014}
+}
+@article{Gerkey2004,
+abstract = {Despite more than a decade of experimental work in multi-robot systems, important theoretical aspects of multi-robot coordination mechanisms have, to date, been largely untreated. To address this issue, we focus on the problem of multi- robot task allocation (MRTA). Most work on MRTA has been ad hoc and empirical, with many coordination architectures having been proposed and validated in a proof-of-concept fashion, but infrequently analyzed. With the goal of bringing objective grounding to this important area of research, we present a formal study of MRTA problems. A domain-independent taxonomy of MRTA problems is given, and it is shown how many such problems can be viewed as instances of other, well-studied, optimization problems. We demonstrate how relevant theory from operations research and combinatorial optimization can be used for analysis and greater understanding of existing approaches to task allocation, and to show how the same theory can be used in the synthesis of new approaches.},
+author = {Gerkey, Brian P. and Matari{\'{c}}, Maja J.},
+doi = {10.1177/0278364904045564},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Gerkey, Matari´cmatari´c - Unknown - A Formal Analysis and Taxonomy of Task Allocation in Multi-Robot Systems.pdf:pdf},
+issn = {02783649},
+journal = {International Journal of Robotics Research},
+keywords = {Coordination,Multi-robot systems,Task allocation,Utility},
+mendeley-groups = {Robots/Task{\&}Plan},
+number = {9},
+pages = {939--954},
+title = {{A formal analysis and taxonomy of task allocation in multi-robot systems}},
+volume = {23},
+year = {2004}
+}
+@article{Jones,
+abstract = {Self-replicating robots represent a new area for prospective advancement in robotics. A self-replicating robot can identify when additional robots are needed to solve a problem or meet user needs, and create them in response to this identified need. This allows robotic systems to respond to changing (or non-predicted) mission needs. Being able to modify the physical system component provides an additional tool for optimizing robotic system performance. This paper begins the process of developing a command and coordination system that makes decisions with the consideration of replication, repair, and retooling capabilities. A high-level algorithm is proposed and qualitatively assessed.},
+author = {Jones, Andrew and Straub, Jeremy and Liang, Steven Y},
+doi = {10.3390/machines5020012},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Jones, Straub, Liang - Unknown - machines Concepts for 3D Printing-Based Self-Replicating Robot Command and Coordination Techniques.pdf:pdf},
+keywords = {3D printing,additive manufacturing,multi-agent system,robot command,robot coordination,robotics,self-replicating robots},
+mendeley-groups = {Robots/Swarm robots/self-replicating,Robots/Swarm robots},
+title = {{Concepts for 3D Printing-Based Self-Replicating Robot Command and Coordination Techniques}},
+url = {www.mdpi.com/journal/machines}
+}
+@article{Suthakorn2003,
+abstract = {The concept of self-replicating machines was introduced more than fifty years ago by John von Neumann. However, to our knowledge a fully autonomous self-replicating robot has not been implemented until now. Here we describe a fully autonomous prototype that demonstrates robotic self replication. This work builds on our previous results in remote-controlled robotic replication and semi-autonomous replicating robotic systems.},
+author = {Suthakorn, J. and Cushing, A. B. and Chirikjian, G. S.},
+doi = {10.1109/AIM.2003.1225085},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Suthakorn, Cushing, Chirikjian - 2003 - An autonomous self-replicating robotic system.pdf:pdf},
+isbn = {0780377591},
+journal = {IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM},
+keywords = {Laboratories,Magnetic sensors,Magnets,Orbital robotics,Production facilities,Prototypes,Robot sensing systems,Robotic assembly,Robotics and automation,Self-replicating machines},
+mendeley-groups = {Robots/Swarm robots/self-replicating,Robots/Swarm robots,Papers/Deep model,Papers/Self-reproducing automaton},
+number = {Aim},
+pages = {137--142},
+title = {{An autonomous self-replicating robotic system}},
+volume = {1},
+year = {2003}
+}
+
+@article{Chirikjian2002,
+abstract = {In this paper, the concept of self-replicating robots (SRRs) is reviewed, and the feasibility of a particular kind of minimalistic SRR is analyzed in the context of lunar resource development. The key issue that will determine the feasibility of this approach is whether or not an autonomous robotic factory can be devised such that it is light enough to be transported to the moon, yet complete in its ability to self-replicate with no other inputs than those resources available on the lunar surface. Self-replication leads to exponential growth, and would allow as few as one initial factory to spawn lunar production of materials and energy on a massive scale. Such capacity would dramatically impact man's ability to explore and colonize space and collect solar energy for terrestrial applications. Our concept of a self-replicating robotic factory consists of four subsystems: 1) multifunctional robots for digging and transportation of materials, and assembly of components during the replication process; 2) materials refining and casting facility; 3) solar energy conversion, storage and transmission; and 4) electromagnetic rail guns for long-distance transportation (for example, for sending materials to low-earth orbit (LEO), or transporting replicated factories to distal points on the moon). Each of these subsystems is described in the context of current technologies, with an emphasis on 1). We build on previous concepts for self-replicating systems, present a simple prototype that demonstrates active mechanical replication, and develop an analytical model of how the proliferation of such systems on the lunar surface would occur.},
+author = {Chirikjian, Gregory S and Zhou, Yu and Suthakorn, Jackrit},
+doi = {10.1109/TMECH.2002.806232},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Chirikjian, Zhou, Suthakorn - 2002 - Self-Replicating Robots for Lunar Development.pdf:pdf},
+isbn = {10834435/02{\$}17.0},
+issn = {10834435},
+journal = {IEEE/ASME Transactions on Mechatronics},
+keywords = {Artificial life,Degenerate diffusion,Lunar resources,Moon,Proliferation,Robot,Rotation group,Self-replication},
+mendeley-groups = {Robots/Swarm robots/self-replicating},
+number = {4},
+pages = {462--472},
+title = {{Self-replicating robots for lunar development}},
+volume = {7},
+year = {2002}
+}
+@article{Jorgensen2005,
+abstract = {This paper describes the mechanical and electrical design of a new lattice based self-reconfigurable robot, called the ATRON. The ATRON system consists of several fully self-contained robot modules, each having their own processing power, power supply, sensors and actuators. The ATRON modules are roughly spheres with equatorial rotation. Each module can be connected to up to eight neighbors through four male and four female connectors. In this paper, we describe the realization of the design, both the mechanics and the electronics. Details on power sharing and power consumption is given. Finally, this paper includes a brief outline of our future work on the ATRON system.},
+author = {Jorgensen, M.W. and Ostergaard, E.H. and Lund, H.H.},
+doi = {10.1109/iros.2004.1389702},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Jorgensen, Ostergaard, Lund - 2005 - Modular ATRON modules for a self-reconfigurable robot.pdf:pdf},
+mendeley-groups = {Robots/Swarm robots},
+pages = {2068--2073},
+title = {{Modular ATRON: modules for a self-reconfigurable robot}},
+year = {2005}
+}
+@article{Tuci2006,
+abstract = {This article illustrates the methods and results of two sets of experiments in which a group of mobile robots, called s-bots, are required to physically connect to each other, that is, to self-assemble, to cope with environmental conditions that prevent them from carrying out their task individually. The first set of experiments is a pioneering study on the utility of self-assembling robots to address relatively complex scenarios, such as cooperative object transport. The results of our work suggest that the s-bots possess hardware characteristics which facilitate the design of control mechanisms for autonomous self-assembly. The control architecture we developed proved particularly successful in guiding the robots engaged in the cooperative transport task. However, the results also showed that some features of the robots' controllers had a disruptive effect on their performances. The second set of experiments is an attempt to enhance the adaptiveness of our multi-robot system. In particular, we aim to synthesise an integrated (i.e., not-modular) decision-making mechanism which allows the s-bot to autonomously decide whether or not environmental contingencies require self-assembly. The results show that it is possible to synthesize, by using evolutionary computation techniques, artificial neural networks that integrate both the mechanisms for sensory-motor coordination and for decision making required by the robots in the context of self-assembly. {\textcopyright} 2006 ACM.},
+author = {Tuci, Elio and Gross, Roderich and Trianni, Vito and Mondada, Francesco and Bonani, Michael and Dorigo, Marco},
+doi = {10.1145/1186778.1186779},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Tuci et al. - 2006 - Cooperation through self-assembly in multi-robot systems.pdf:pdf},
+issn = {15564665},
+journal = {ACM Transactions on Autonomous and Adaptive Systems},
+keywords = {Artificial neural networks,Evolutionary algorithms,Evolutionary robotics,Self-assembly,Swarm intelligence,Swarm robotics},
+mendeley-groups = {Robots/Swarm robots},
+number = {2},
+pages = {115--150},
+title = {{Cooperation through self-assembly in multi-robot systems}},
+url = {http://portal.acm.org/citation.cfm?doid=1186778.1186779},
+volume = {1},
+year = {2006}
+}
+@article{Kaloutsakis2011,
+abstract = {This paper presents the development of a self-replicating mobile robot that functions by undergoing stochastic motions. The robot functions hierarchically. There are three stages in this hierarchy: (1) An initial pool of feed modules/parts together with one functional basic robot; (2) a collection of basic robots that are spontaneously formed out of these parts as a result of a chain reaction induced by stochastic motion of the initial seed robot at stage 1; (3) complex formations of joined basic robots from stage 2. In the first part of this paper we demonstrate basic stochastic self-replication in unstructured environments. A single functional robot moves around at random in a sea of stock modules and catalyzes the conversion of these modules into replicas. In the second part of the paper, the robots are upgraded with a layer that enables mechanical connections between robots. The replicas can then connect to each other and aggregate. Finally, self-reconfigurability is presented for two robotic aggregations.},
+author = {Kaloutsakis, Georgios and Chirikjian, Gregory S},
+doi = {10.1017/S0263574710000780},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Kaloutsakis, Chirikjian - 2011 - A stochastic self-replicating robot capable of hierarchical assembly.pdf:pdf},
+journal = {Robotica},
+keywords = {Manufacturing,Mechatronic systems,Mobile robots,Modular robots,Multi-robot systems,Robotic self-diagnosis,Robotic self-replication,Self-repair,Swarm robotics},
+mendeley-groups = {Robots/Swarm robots/self-replicating},
+pages = {137--152},
+title = {{A stochastic self-replicating robot capable of hierarchical assembly}},
+url = {https://doi.org/10.1017/S0263574710000780},
+volume = {29},
+year = {2011}
+}
+@article{Suthakorn2003,
+abstract = {The concept of self-replicating machines was introduced more than fifty years ago by John von Neumann. However, to our knowledge a fully autonomous self-replicating robot has not been implemented until now. Here we describe a fully autonomous prototype that demonstrates robotic self replication. This work builds on our previous results in remote-controlled robotic replication and semi-autonomous replicating robotic systems.},
+author = {Suthakorn, J. and Cushing, A. B. and Chirikjian, G. S.},
+doi = {10.1109/AIM.2003.1225085},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Suthakorn, Cushing, Chirikjian - 2003 - An autonomous self-replicating robotic system.pdf:pdf},
+isbn = {0780377591},
+journal = {IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM},
+keywords = {Laboratories,Magnetic sensors,Magnets,Orbital robotics,Production facilities,Prototypes,Robot sensing systems,Robotic assembly,Robotics and automation,Self-replicating machines},
+mendeley-groups = {Robots/Swarm robots/self-replicating,Robots/Swarm robots,Papers/Deep model,Papers/Self-reproducing automaton},
+number = {Aim},
+pages = {137--142},
+title = {{An autonomous self-replicating robotic system}},
+volume = {1},
+year = {2003}
+}
+@article{Butler2003,
+abstract = {In this paper, we describe a set of distributed algorithms for self-reconfiguring modular robots that allow them to explore an area in parallel. The algorithms are based on geometric rules that each module evaluates independently relative to its local neighborhood. This paper concentrates on developing algorithms within this framework to enable travel over the widest variety of terrain In particular, we show how to perform straight-line motion, turning while on obstacles, climbing over tall obstacles, and tunneling under overhangs, all of which work for groups of arbitrary size. This last feature is important, as it also allows a large system of self-reconfiguring modules to divide up into several groups of various sizes, each of which is equally capable of motion and participation in the overall group task. We also discuss implementations and ways to improve efficiency and switching between tasks.},
+author = {Butler, Zack and Rus, Daniela},
+doi = {10.1109/CIRA.2003.1222296},
+file = {:home/qiqi/Downloads/papers/Distributed Locomotion Algorithms for Self-Reconfigurable Robots Operating on Rough Terrain.pdf:pdf},
+isbn = {0780378660},
+journal = {Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA},
+mendeley-groups = {Robots/Swarm robots/self-replicating},
+pages = {880--885},
+title = {{Distributed locomotion algorithms for self-reconfigurable robots operating on rough terrain}},
+volume = {2},
+year = {2003}
+}
+@article{Menezes2012,
+abstract = {This article is motivated by the need to minimize the number of elements required to establish a self-reproducing system. One such system is a self-reproducing extraterrestrial robotic colony, which reduces the launch payload mass for space exploration compared to current mission configurations. In this work, self-reproduction is achieved by the actions of a robot on available resources. An important consideration for the establishment of any self-reproducing system is the identification of a seed, for instance, a set of resources and a set of robots that utilize them to produce all of the robots in the colony. This article outlines a novel algorithm to determine an optimal seed for self-reproducing systems, with application to a self-reproducing extraterrestrial robotic colony. Optimality is understood as the minimization of a cost function of the resources and, in this article, the robots. Since artificial self-reproduction is currently an open problem, the algorithm is illustrated with a simple robotic self-replicating system from the literature and with a more complicated self-reproducing example from nature. {\textcopyright} 2011 Massachusetts Institute of Technology.},
+author = {Menezes, Amor A. and Kabamba, Pierre T.},
+doi = {10.1162/artl_a_00048},
+file = {:home/qiqi/Downloads/papers/Optimal Seeding of Self-Reproducing Systems.pdf:pdf},
+issn = {10645462},
+journal = {Artificial Life},
+keywords = {Combinatorial optimization,discrete mathematics,graph algorithm applications,seed identification,self-reproducing systems,space robotics},
+mendeley-groups = {Robots/Swarm robots/self-replicating},
+number = {1},
+pages = {27--51},
+title = {{Optimal seeding of self-reproducing systems}},
+volume = {18},
+year = {2012}
+}
+@article{Yan2013,
+abstract = {In the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper.},
+author = {Yan, Zhi and Jouandeau, Nicolas and Cherif, Arab Ali},
+doi = {10.5772/57313},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Yan, Jouandeau, Cherif - 2013 - International Journal of Advanced Robotic Systems A Survey and Analysis of Multi-Robot Coordination Regu.pdf:pdf},
+keywords = {Coordination,Motion Planning,Multi-Robot System,Task Planning},
+mendeley-groups = {Robots/Swarm robots/self-replicating,Robots/Swarm robots},
+title = {{A Survey and Analysis of Multi-Robot Coordination Regular Paper}},
+url = {www.intechopen.com},
+year = {2013}
+}
+@article{Jones,
+abstract = {Self-replicating robots represent a new area for prospective advancement in robotics. A self-replicating robot can identify when additional robots are needed to solve a problem or meet user needs, and create them in response to this identified need. This allows robotic systems to respond to changing (or non-predicted) mission needs. Being able to modify the physical system component provides an additional tool for optimizing robotic system performance. This paper begins the process of developing a command and coordination system that makes decisions with the consideration of replication, repair, and retooling capabilities. A high-level algorithm is proposed and qualitatively assessed.},
+author = {Jones, Andrew and Straub, Jeremy and Liang, Steven Y},
+doi = {10.3390/machines5020012},
+file = {:home/qiqi/.local/share/data/Mendeley Ltd./Mendeley Desktop/Downloaded/Jones, Straub, Liang - Unknown - machines Concepts for 3D Printing-Based Self-Replicating Robot Command and Coordination Techniques.pdf:pdf},
+keywords = {3D printing,additive manufacturing,multi-agent system,robot command,robot coordination,robotics,self-replicating robots},
+mendeley-groups = {Robots/Swarm robots/self-replicating,Robots/Swarm robots,Papers/Self-reproducing automaton},
+title = {{Concepts for 3D Printing-Based Self-Replicating Robot Command and Coordination Techniques}},
+url = {www.mdpi.com/journal/machines}
+}
+
+@article{Polygerinos2015ModelingOS,
+  title={Modeling of Soft Fiber-Reinforced Bending Actuators},
+  author={Panagiotis Polygerinos and Zheng Wang and Johannes T. B. Overvelde and Kevin C. Galloway and Robert J. Wood and Katia Bertoldi and Conor James Walsh},
+  journal={IEEE Transactions on Robotics},
+  year={2015},
+  volume={31},
+  pages={778-789}
+}
+
+@article{Suthakorn2003-1,
+abstract = {The concept of self-replicating machines was introduced more than fifty years ago by John von Neumann. However, a fully autonomous self-replicating robot has yet to be implemented. This paper discusses our ongoing research on self-replicating robots. Here we describe a semi-autonomous prototype that can demonstrate replication under human supervision. This work builds on our previous results in remote-controlled robotic replication with the added feature that many subtasks in the replication process are now autonomously performed by the robot. We believe this to be an important step in the realization of fully autonomous self-replicating robots.},
+author = {Suthakorn, Jackrit and Kwon, Yong T. and Chirikjian, Gregory S.},
+doi = {10.1109/CIRA.2003.1222279},
+file = {:Users/zhaowanqi/Library/Application Support/Mendeley Desktop/Downloaded/Suthakorn, Kwon, Chirikjian - 2003 - A semi-autonomous replicating robotic system.pdf:pdf},
+isbn = {0780378660},
+journal = {Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA},
+keywords = {Artificial life,Modular robots,Robot,Self-replication,Service robots},
+mendeley-groups = {Robots/Swarm robots/self-replicating,Robots/Role model based domain-specific modeling framework for mutli-robot applications},
+pages = {776--781},
+title = {{A semi-autonomous replicating robotic system}},
+volume = {2},
+year = {2003}
+}
+@inproceedings{Ellery2016,
+abstract = {Recent developments in three-dimensional printing technology have introduced the prospect of self-replication in the context of robotic in situ resource utilization on the moon. The value of three-dimensional printing lies in its potential to implement universal construction. A universal constructor is a machine capable of fabricating any physical product given an appropriate program of instructions, suitable raw materials, and a source of energy in an appropriate form. Such physical products include a copy of itself; a universal constructor is by definition a selfreplicating machine. A step in this direction is represented by the RepRap three-dimensional printer that can print copies of its own plastic components. The three-dimensional printing of actuators and associated control electronics would represent an existence proof that an appropriately designed robotic three-dimensional printer system would constitute a universal constructor. In this paper, preliminary attempts have been outlined to develop self-replicating machines by addressing the three-dimensional-printable actuator and electronics aspects within the materials limits imposed by the moon. It is concluded that physical self-replicating machines are within reach. This lunar infrastructure offers space-based geoengineering solutions in the short term and solar power satellite solutions in the long term to the global climate crisis.},
+author = {Ellery, Alex},
+booktitle = {Journal of Spacecraft and Rockets},
+doi = {10.2514/1.A33409},
+file = {:Users/zhaowanqi/Library/Application Support/Mendeley Desktop/Downloaded/Ellery - 2015 - Are Self-Replicating Machines Feasible.pdf:pdf},
+issn = {00224650},
+mendeley-groups = {Robots/Swarm robots/self-replicating},
+number = {2},
+pages = {317--327},
+title = {{Are Self-Replicating machines feasible?}},
+url = {http://arc.aiaa.org},
+volume = {53},
+year = {2016}
+}
+
+@inproceedings{Lee1996PrinciplesAM,
+  title={Principles and methods of testing finite state machines-a survey},
+  author={David Lee and Mihalis Yannakakis},
+  year={1996}
+}
+
+@article{Atkinson2009AFI,
+  title={A Flexible Infrastructure for Multilevel Language Engineering},
+  author={Colin Atkinson and Matthias Gutheil and Bastian Kennel},
+  journal={IEEE Transactions on Software Engineering},
+  year={2009},
+  volume={35},
+  pages={742-755}
+}
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