literature swarm robotics communication

8/10/2019 literature swarm robotics communication

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@InProceedings{akdemir2011emerging, Title = {An emerging threat: eve meets a robot}, Author = {Akdemir, Kahraman D and Karakoyunlu, Deniz and Padir, Taskin and Sunar, Berk}, Booktitle = {Trusted Systems}, Year = {2011}, Pages = {271--289}, Publisher = {Springer},

__markedentry = {[Florian:5]}, Abstract = {In this work, we study the emerging security threats in aquickly proliferating eld: robotics. The next generation robots embodymost of the networking and computing components we normally use foreveryday computing. Thus, the next generation robots virtually inheritall of the security weaknesses we are struggling with today. To makethings worse, vulnerabilities in robots are much more signicant, as theyphysically interact with their surroundings which include human beings.In this paper, we rst provide a classication of potential physical attackson robots. In addition, we outline a concrete active attack and propose

a countermeasure.}, File = {:papers\\2011_An Emerging Threat\; Eve Meets a Robot.pdf:PDF}, Keywords = {Side-channel attacks, fault injection, informationleakage, countermeasures, robotics}, Review = {An Emerging Threat: Eve Meets a Robot

(Work-in-Progress)

Kahraman D. Akdemir, Deniz Karakoyunlu, Taskin Padir, and Berk Sunar

Department of Electrical and Computer Engineering, Worcester Polytechnic Institute,

100 Institute Road, Worcester, MA 01609, USA

{kahraman,deniz,tpadir,sunar}@wpi.edu

Abstract. In this work, we study the emerging security threats in aquickly proliferating eld: robotics. The next generation robots embodymost of the networking and computing components we normally use foreveryday computing. Thus, the next generation robots virtually inheritall of the security weaknesses we are struggling with today. To makethings worse, vulnerabilities in robots are much more signicant, as theyphysically interact with their surroundings which include human beings.In this paper, we rst provide a classication of potential physical attackson robots. In addition, we outline a concrete active attack and propose

a countermeasure.

Keywords: Side-channel attacks, fault injection, information leakage,countermeasures, robotics.

1 Introduction

Since the development of the rst modern operating systems and computer net-works we have witnessed the discovery of numerous vulnerabilities and secu-rity issues. We are accustomed to attacks targeting platforms at the operating


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system, network or at the implementation levels. For example, viruses, worms,malware, privilege escalation attacks, denial-of-service attacks, intrusion, SQLinjection, re-routing, cold-boot attacks, side-channel attacks, manufacturer at-tacks etc. are commonly known types of attacks. These attacks target essentiallyall components of the greater network, ranging from high end platforms such asdesktops, laptops, pay-tv-boxes, gaming platforms, to low-end devices such asnetbooks, cell-phones, RFIDs, and internet enabled embedded devices. What iscommon to all of these platforms is that the harm done in an attack is isolatedto loss of service or of digital data, or nancial loss or to the violation of theindividual's privacy. Only on rare occasions such attacks may escalate to a lifethreatening situation. For instance, a number of such attacks have appeared re-cently that target medical devices (e.g., see [14]). While such attacks are fairlylimited, these studies have drawn a signicant level of attention from both re-searchers and the public primarily due to the direct harm inicted on humans.

L. Chen and M. Yung (Eds.): INTRUST 2010, LNCS 6802, pp. 271289, 2011.c Springer-Verlag Berlin Heidelberg 2011}}

@Article{alami1998multi, Title = {Multi-robot cooperation in the MARTHA project}, Author = {Alami, Rachid and Fleury, Sara and Herrb, Matthieuand Ingrand, F{\

e}lix and Robert, Fr{\

e}d{\

e}ric},

Journal = {Robotics \& Automation Magazine, IEEE}, Year = {1998}, Number = {1}, Pages = {36--47}, Volume = {5},

__markedentry = {[Florian:1]}, File = {:papers\\1998_Multi-robot cooperation in the MARTHA project.pdf:PDF}, Publisher = {IEEE}}

@Article{ampatzis2008evolution,

Title = {Evolution of signaling in a multi-robot system: Categorization and communication}, Author = {Ampatzis, Christos and Tuci, Elio and Trianni, Vito and Dorigo, Marco}, Journal = {Adaptive Behavior}, Year = {2008}, Number = {1}, Pages = {5--26}, Volume = {16},

__markedentry = {[Florian:]}, File = {:papers\\2008_Evolution of signaling in a multi-robot system\; Categorization and communication.pdf:PDF},

Publisher = {SAGE Publications}}

@InProceedings{ampatzis2005evolving, Title = {Evolving communicating agents that integrate information over time: a real robot experiment}, Author = {Ampatzis, Christos and Tuci, Elio and Trianni, Vito and Dorigo, Marco}, Booktitle = {CD-ROM Proceedings of the 7th International Conference on Artificial Evolution (EA 2005)},


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Year = {2005}, Organization = {Springer},

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@InProceedings{arkin2002line, Title = {Line-of-sight constrained exploration for reactivemultiagent robotic teams}, Author = {Arkin, Ronald C and Diaz, Jonathan}, Booktitle = {Advanced Motion Control, 2002. 7th International Workshop on}, Year = {2002}, Organization = {IEEE}, Pages = {455--461},

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@Article{baldassarre2006distributed, Title = {Distributed coordination of simulated robots basedon self-organization}, Author = {Baldassarre, Gianluca and Parisi, Domenico and Nolfi, Stefano}, Journal = {Artificial Life}, Year = {2006}, Number = {3}, Pages = {289--311}, Volume = {12},

__markedentry = {[Florian:4]}, Publisher = {MIT Press}}

@Article{bredeche2012environment, Title = {Environment-driven distributed evolutionary adaptation in a population of autonomous robotic agents}, Author = {Bredeche, Nicolas and Montanier, Jean-Marc and Liu, Wenguo and Winfield, Alan FT}, Journal = {Mathematical and Computer Modelling of Dynamical S


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ystems}, Year = {2012}, Number = {1}, Pages = {101--129}, Volume = {18},

__markedentry = {[Florian:]}, File = {:papers\\2011_Environment-driven Distributed Evolutionary Adaptation in a Population of Autonomous Robotic Agents.pdf:PDF}, Keywords = {Evolutionary Adaptation, Robotic Swarm, Online Distributed learning, Artificial Evolution, Implicit fitness, Evolutionary Robotics, Robustness to Environmental Changes, Emergence of Consensus}, Publisher = {Taylor \& Francis}, Review = {December 18, 2010 23:0 Mathematical and Computer Modelling of Dynamical Systems medea-journal-final

Author manuscript, published in "Mathematical and Computer Modelling of Dynamical Systems (2011)"Mathematical and Computer Modelling of Dynamical SystemsVol. 00, No. 00, Month 200x, 127

RESEARCH ARTICLE

Environment-driven Distributed Evolutionary Adaptation

in a Population of Autonomous Robotic Agents

Nicolas Bredechea,, Jean-Marc Montaniera, Wenguo Liub and Alan F.T. Winfieldb

aTAO - Univ. Paris-Sud, INRIA, CNRS - F-91405 Orsay, France; bBristol RoboticsLaboratory, University of the West of England, Bristol, UK, BS16 1QY.

(Received 00 Month 200x; final version received 00 Month 200x)

This paper is concerned with a fixed-size population of autonomous agents facingunknown,

possibly changing, environments. The motivation is to design an embodied evolutionary al-gorithm that can cope with the implicit fitness function hidden in the environment so as toprovide adaptation in the long run at the level of the population. The proposedalgorithm,termed mEDEA, is shown to be both efficient in an unknown environment and robusttoabrupt and unpredicted changes in the environment. The emergence of consensus towardsspecific behavioural strategies is examined, with a particular focus on algorithmic stability.To conclude the paper a real world implementation of the algorithm in a populati

on of 20real-world e-puck robots is described and the algorithm is shown to perform remarkably wellin the face of environmental constraints and technical issues.

Keywords: Evolutionary Adaptation, Robotic Swarm, Online Distributed learning,Artificial Evolution, Implicit fitness, Evolutionary Robotics, Robustness to EnvironmentalChanges, Emergence of Consensus.


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AMS Subject Classification: 68-99, 68T01, 68T40, 68W15, 68W25, 93C40

1. Introduction

With the advent of reliable and powerful software and hardware at reasonable cost,it is now possible to study the dynamics of large groups of autonomous agentswithin various environments. Indeed, much work has already addressed the issueof designing efficient adaptive behavioral strategies in populations of agents,withvery different approaches and motivations [6, 33]. One particularly interestingsce-nario is a population of robotic units that are immersed in a completely unknownenvironment, yet still manage to survive, then moved into a different environmentrequiring very different behavioural strategies. In this paper we are interestedina fixed-size population of autonomous physical agents using local communication,such as autonomous robots, facing unknown and/or dynamic environments. Thisclass of problems typically applies when the environment is unknown to the humandesigner until the population of agents is actually made operational in the realsit-uation [1], or whenever the environment is expected to change during operationwith no indication of when and how these changes will impact survival strategies

.

The challenge is to design a distributed online optimisation algorithm addressingagent self-adaptation in the long term, that is able to successfully manage an im-plicit pressure resulting from environmental properties and algorithmic constraintswith regard to the optimisation process. While the lack of explicit objective func-

Corresponding author. Email: [email protected]

ISSN: 1387-3954 print/ISSN 1744-5051 onlinec 200x Taylor & FrancisDOI: 10.1080/1387395YYxxxxxxxxhttp://www.informaworld.com

inria-00531450, version 1 - 17 Feb 2011}}

@InProceedings{Chai6858, Title = {6.858: Hacking Bluetooth}, Author = {Elaina Chai and Ben Deardorff and Cathy Wu}, Year = {2012},

__markedentry = {[Florian:5]}, File = {:papers\\2012_6.858 Hacking Bluetooth.pdf:PDF}, Review = {6.858: Hacking Bluetooth

Elaina Chai Ben Deardorff Cathy [email protected] [email protected] [email protected]

09 December 2012

Abstract


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After learning about and analyzing the security of Bluetooth, it was clear tous that Bluetooth sniffing tools are still substandard compared to those availablefor sniffing other types of wireless traffic like WiFi. This makes it harder forhack-ers to develop exploits for Bluetooth devices but also makes it more difficult forsecurity researchers to realistically evaluate Bluetooth security. We decided thatthe best way to address this problem is to continue development of the softwarefor the Ubertooth module, currently the most cost effective hardware device forsniffing Bluetooth packets. In this paper, we highlight the fact that Bluetoothisa widespread technology with real privacy and security implications. Furthermore,we explore the current capabilities of using inexpensive open source software andhardware to examine data from arbitrary Bluetooth devices. We have also imple-mented piconet following in the Kismet-Ubertooth plugin, making it an even moreeffective tool for future researchers in this area. Our implementation can be foundat https://github.com/cathywu/6858-kismet-ubertooth.

1}}

@InCollection{cianci2007communication, Title = {Communication in a swarm of miniature robots: Thee-puck as an educational tool for swarm robotics}, Author = {Cianci, Christopher M and Raemy, Xavier and Pugh,Jim and Martinoli, Alcherio}, Booktitle = {Swarm Robotics}, Publisher = {Springer}, Year = {2007}, Pages = {103--115},

__markedentry = {[Florian:]}, File = {:papers\\2007_Communication in a swarm of miniature robots The e-puck as an educational tool for swarm robotics.pdf:PDF}}

@InCollection{ferrante2013socially, Title = {Socially-mediated negotiation for obstacle avoidance in collective transport}, Author = {Ferrante, Eliseo and Brambilla, Manuele and Birattari, Mauro and Dorigo, Marco}, Booktitle = {Distributed Autonomous Robotic Systems}, Publisher = {Springer}, Year = {2013},

Pages = {571--583},

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@Article{Floreano2007, Title = {Evolutionary Conditions for the Emergence of Communication in Robots},


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@InProceedings{gross2004group, Title = {Group transport of an object to a target that onlysome group members may sense}, Author = {Gro{\ss}, Roderich and Dorigo, Marco}, Booktitle = {Parallel Problem Solving from Nature-PPSN VIII}, Year = {2004}, Organization = {Springer},


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@Article{haasdijk2013individual, Title = {Individual, social and evolutionary adaptation incollective systems}, Author = {Haasdijk, Evert and Eiben, AE and Winfield, Alan FT}, Year = {2013},

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Fiona Higgins, Allan Tomlinson and Keith M.Martin

Technical ReportRHUL-MA-2008-19

October 2008

Department of MathematicsRoyal Holloway, University of LondonEgham, Surrey TW20 0EX, England

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@Article{DBLP:journals/corr/abs-1109-3617, Title = {IR-based Communication and Perception in Microrobotic Swarms}, Author = {Sergey Kornienko and Olga Kornienko}, Journal = {CoRR}, Year = {2011},


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Volume = {abs/1109.3617},

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__markedentry = {[Florian:4]}, Abstract = {Bluetooth (over IEEE 802.15.1), ultra-wideband Onthe other hand, for accessing networks and services


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(UWB, over IEEE 802.15.3), ZigBee (over IEEE 802.15.4), and without cables, wireless communications is a fast-growingWi-Fi (over IEEE 802.11) are four protocol standards for short-range wireless communications with low power consumption. technology to providethe flexibility and mobility [3].From an application point of view, Bluetooth is intended for a Obviously, reducing the cable restriction is one of the benefitscordless mouse, keyboard, and hands-free headset, UWB is of wireless with respect to cabled devices. Other benefitsoriented to high-bandwidth multimedia links, ZigBee is designed include the dynamic network formation, low cost, and easyfor reliable wirelessly networked monitoring and control deployment. General speaking, the short-range wireless scenenetworks, while Wi-Fi is directed at computer-to-computerconnections as an extension or substitution of cabled networks. In is currentlyheld by four protocols: the Bluetooth, and UWB,this paper, we provide a study of these popular wireless ZigBee, and Wi-Fi, which are corresponding to the IEEEcommunication standards, evaluating their main features and 802.15.1, 802.15.3,802.15.4, and 802.11a/b/g standards,behaviors in terms of various metrics, including the transmission respectively.IEEE defines the physical (PHY) and MACtime, data coding efficiency, complexity, and power consumption. layers for wireless communications over an action range

It is believed that the comparison presented in this paper wouldbenefit application engineers in selecting an appropriate protocol. around 10-100 meters. For Bluetooth and Wi-Fi, Ferro and }, File = {:papers\\2007_A Comparative Study of wireless protocols Bluetooth, UWB, ZigBee, and Wi-Fi.pdf:PDF}, Review = {The 33rd Annual Conference of the IEEE IndustrialElectronics Society (IECON)Nov. 5-8, 2007, Taipei, Taiwan

A Comparative Study of Wireless Protocols:Bluetooth, UWB, ZigBee, and Wi-Fi

Jin-Shyan Lee, Yu-Wei Su, and Chung-Chou Shen

Information & Communications Research LabsIndustrial Technology Research Institute (ITRI)

Hsinchu, [email protected]

Abstract Bluetooth (over IEEE 802.15.1), ultra-wideband On the other hand, for accessing networks and services

(UWB, over IEEE 802.15.3), ZigBee (over IEEE 802.15.4), and without cables, wireless communications is a fast-growingWi-Fi (over IEEE 802.11) are four protocol standards for short-range wireless communications with low power consumption. technology to providethe flexibility and mobility [3].From an application point of view, Bluetooth is intended for a Obviously, reducing the cable restriction is one of the benefitscordless mouse, keyboard, and hands-free headset, UWB is of wireless with respect to cabled devices. Other benefitsoriented to high-bandwidth multimedia links, ZigBee is designed include the dyna


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mic network formation, low cost, and easyfor reliable wirelessly networked monitoring and control deployment. General speaking, the short-range wireless scenenetworks, while Wi-Fi is directed at computer-to-computerconnections as an extension or substitution of cabled networks. In is currentlyheld by four protocols: the Bluetooth, and UWB,this paper, we provide a study of these popular wireless ZigBee, and Wi-Fi, which are corresponding to the IEEEcommunication standards, evaluating their main features and 802.15.1, 802.15.3,802.15.4, and 802.11a/b/g standards,behaviors in terms of various metrics, including the transmission respectively.IEEE defines the physical (PHY) and MACtime, data coding efficiency, complexity, and power consumption. layers for wireless communications over an action rangeIt is believed that the comparison presented in this paper wouldbenefit application engineers in selecting an appropriate protocol. around 10-100 meters. For Bluetooth and Wi-Fi, Ferro and

Potorti [4] compared their main features and behaviors in termsIndex Terms Wireless protocols, Bluetooth, ultra-wideband of various metrics, including capacity, network topology,

(UWB), ZigBee, Wi-Fi, short-range communications.security, quality of service support, and power consumption. In

[5], Wang et al. compared the MAC of IEEE 802.11e andI. INTRODUCTION IEEE 802.15.3. Their results showed that the throughput

difference between them is quite small. In addition, the powerIn the past decades, factory automation has been developed management of 802.15.3 is easier than that of 802.11e. For

worldwide into a very attractive research area. It incorporates ZigBee and Bluetooth, Baker [6] studied their strengths anddifferent modern disciplines including communication, weaknesses for industrialapplications, and claimed thatinformation, computer, control, sensor, and actuator ZigBee over 802.15.4 protoc

ol can meet a wider variety of realengineering in an integrated way, leading to new solutions, industrial needs than Bluetooth due to its long-term batterybetter performance and complete systems. One of the operation, greater useful range, flexibility in a number ofincreasingly important components in factory automation is the dimensions, and reliability of the mesh networking architecture.industrial communication [1]. For interconnection purposes, a In this paper, after an overview of the mentioned four short-factory automation system can be combined with various range wireless protocols,we attempt to make a preliminarysensors, controllers, and heterogeneous machines using a comparison of them andthen specifically study their

common message specification. Many different network types transmission time, data coding efficiency, protocol complexity,have been promoted for use on a shop floor, including control and power consumption. The rest of this paper is organized asarea network (CAN), Process fieldbus (Profibus), Modbus, and follows. Section IIbriefly introduces the wireless protocolsso on. However, how to select a suitable network standard for a including Bluetooth, UWB, ZigBee, and Wi-Fi. Next, aparticular application is a critical issue to the industrial comprehensive evaluation of them is described in Section III.


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engineers. Lain et al. [2] evaluated the Ethernet (carrier sense Then, in Section IV, the complexity and power consumptionmultiple access with collision detection, CSMA/CD bus), are compared based on IEEE standards and commercial off-ControlNet (token-passing bus), and DeviceNet (CSMA with the-shelf wireless products, respectively. Finally, Section Varbitration on message priority, CSMA/AMP bus) for concludes this paper.networked control applications. After a detailed discussion ofthe medium access control (MAC) sublayer protocol for eachnetwork, they studied the key parameters of the corresponding II. WIRELESS PROTOCOLSnetwork when used in a control situation, including network This section introduces the Bluetooth, UWB, ZigBee, andutilization and time delays. Wi-Fi protocols, which corresponds to the IEEE 802.15.1,

1-4244-0783-4/07/$20.00 2007 IEEE 46}}

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@InCollection{nolfi2010evolving,

Title = {Evolving Communication in Embodied Agents: Assessment and Open Challenges}, Author = {Nolfi, Stefano and Mirolli, Marco}, Booktitle = {Evolution of Communication and Language in Embodied Agents}, Publisher = {Springer Berlin Heidelberg}, Year = {2010}, Editor = {Nolfi, Stefano and Mirolli, Marco}, Pages = {215-220},

__markedentry = {[Florian:]}, Doi = {10.1007/978-3-642-01250-1_12}, File = {:papers\\2010_Evolving Communication in Embodied A

gents Assessment and Open Challenges.pdf:PDF}, ISBN = {978-3-642-01249-5}, Language = {English}, Url = {http://dx.doi.org/10.1007/978-3-642-01250-1_12}}

@InProceedings{Parker, Title = {Active versus Passive Expression of Preference inthe Control of Multiple-Robot Decision-Making}, Author = {Chris A. C. Parker and Hong Zhang and Department of Computing and Science},

__markedentry = {[Florian:3]},

Abstract = {Just like their solitary counterparts, multiple-robot The supervisor then delegates the various roles required bysystems must be able to make decisions in response to their the selected play tothe various robots on the team.environment. However, with a multiple-robot system, one musttake care to ensure that the individual rob Both of these decision-making strategies emphasize theots that composea system make their decisions in concert with each other. We need for team-leveldecisions to be unanimous. It is of no usedesire decisions to be made at the system level. In this paper we if a few robot


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s devise the ideal solution to some problem ifinvestigate four different mechanisms to allow individual robots the remainder of their system does not recognize the decisionwithin a system to express their preference for a particular and carries out a different solution, especially if the two (orsolution to a system-level problem. All four mechanisms consis- more) solutionsare in conflict with each other.tently produced unanimous decisions, but had varying abilityto produce unanimous decisions of good quality. An approach In our previous workon this subject, we have taken athat we refer to as passive expression of preference performed bottom-up approach to the multiple-robot decision-makingthe best, but had to be tuned to the particular problem being problem as well. We developed and implemented a decision-solved. A mechanism that we refer to as active expression making algorithm basedon the nest site selection strategy ofof preference exhibited very good performance and required a particular speciesof ant, of which we give an overview inno problem specific tuning, which makes it more universallyapplicable to the multiple-robot decision-making problem Section II. The individual ants express their preference for.}, File = {:papers\\2005_Active versus Passive Expression ofPreference in the Control of Multiple-Robot Decision-Making.pdf:PDF}, Review = {description evolution sim real platform com_type c

om_medium task}}

@InProceedings{Quinn2001, Title = {Evolving Communication without Dedicated Communication Channels}, Author = {Matt Quinn}, Booktitle = {ECAL 2001}, Year = {2001}, Editor = {J. Kelemen and P. Sosk}, Pages = {357366}, Publisher = {Springer}, Series = {LNAI},

Volume = {2159},

__markedentry = {[Florian:1]}, Abstract = {Articial Life models have consistently implementedcom-munication as an exchange of signals over dedicated and functionallyisolated channels. I argue that such a feature prevents models from pro-viding a satisfactory account of the origins of communication and presenta model in which there are no dedicated channels. Agents controlled byneural networks and equipped with proximity sensors and wheels are pre-sented with a co-ordinated movement task. It is observed that functional,but non-communicative, behaviours which evolve in the early stages ofthe simulation both make possible, and form the basis of, the commu-

nicative behaviour which subsequently evolves.}, File = {:papers\\2001_Evolving Communication without Dedicated Communication Channels.pdf:PDF}, Review = {Evolving Communication without DedicatedCommunication Channels

Matt Quinn

Centre for Computational Neuroscience and Robotics,University of Sussex, Brighton, U.K.


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[email protected]

Abstract. Articial Life models have consistently implemented com-munication as an exchange of signals over dedicated and functionallyisolated channels. I argue that such a feature prevents models from pro-viding a satisfactory account of the origins of communication and presenta model in which there are no dedicated channels. Agents controlled byneural networks and equipped with proximity sensors and wheels are pre-sented with a co-ordinated movement task. It is observed that functional,but non-communicative, behaviours which evolve in the early stages ofthe simulation both make possible, and form the basis of, the commu-nicative behaviour which subsequently evolves.

1 Introduction

The question of how communicative behaviour might have originated is an in-teresting one, and the transition from non-communicative to communicative be-haviour has long been of interest to ethologists [2,4]. Articial Life techniques,such as agent-based simulation models, are potentially useful tools for exploringquestions and hypotheses related to this transition. In particular, they enablethe simulation of co-evolving, interacting organisms at the level of changes inbehaviour and perception. There are a number of models in the ALife litera-

ture which simulate the evolution of an organised communication system in aninitially non-communicating population of agents (e.g., [11,6,1,5,3]). In all thesemodels, communication is restricted to an exchange of signals over dedicatedand functionally isolated communication channels. This feature, I wish to argue,severely reduces the explanatory value of a model of the evolutionary origins ofcommunication in natural systems.

Dedicated channels are a reasonable feature of a model which assumes thatindividuals are already able to communicate. However, explaining the origins ofcommunicative behaviour typically involves explaining how it could have evolvedfrom originally non-communicative behaviours [2,4,7]. This kind of explanationis not possible with a model which restricts all potential communication to ded-

icated and functionally isolated channels. However, this problem is avoided if amodel allows potentially communicative behaviour to be functional (and henceacquire selective value) in contexts other than communication. In order to il-lustrate this point, I present a model in which there are no dedicated com-munication channels. Agents are evolved to perform a non-trivial co-ordinated

J. Kelemen and P. Sosk (Eds.): ECAL 2001, LNAI 2159, pp. 357366, 2001.c Springer-Verlag Berlin Heidelberg 2001}}

@InProceedings{Fox2000, Title = {Coordination for Multi-Robot Exploration and Mapping},

Author = {Reid Simmons,David Apfelbaum, Wolfram Burgard, Dieter Fox and Mark Moors and Sebastian Thrun and Hkan Younes}, Year = {2000}, Publisher = {From: AAAI-00 Proceedings. Copyright 2000, AAAI (www.aaai.org). All rights reserved.},

__markedentry = {[Florian:1]}, Abstract = {optimally is intractable, we present a greedy approach thatperforms quite well, in practice.},


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File = {:papers\\2000_Coordination for multi-robot exploration and mapping.pdf:PDF}, Review = {From: AAAI-00 Proceedings. Copyright 2000, AAAI (www.aaai.org). All rights reserved.

Coordination for Multi-Robot Exploration and MappingReid Simmons, David Apfelbaum, Wolfram Burgard1,

Dieter Fox, Mark Moors2, Sebastian Thrun, Hkan YounesSchool of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213

1Department of Computer Science, University of Freiburg, 79110 Freiburg, Germany2Department of Computer Science III, University of Bonn, 53117 Bonn, Germany

Abstract optimally is intractable, we present a greedy approach thatperforms quite well, in practice.

This paper addresses the problem of exploration andmapping of an unknown environment by multiple robots Our basic approach to bothcoordination problems is.The mapping algorithm is an on-line approach to similar: Distribute most of thecomputation amongst thelikelihood maximization that uses hill climbing to find individual robots and asynchronously integrate their results

maps that are maximally consistent with sensor data and by performing some global computations over the data. Forodometry. The exploration algorithm explicitly coordinates instance, each robotprocesses its own laser data to create athe robots. It tries to maximize overall utility by minimizing consistent localmap. A central mapper module thenthe potential f integrates the local maps to create a consistent global map.or overlap in information gain amongst thevarious robots. For both the exploration and mapping The local mappers reduce uncertainty in the data,algorithms, most of the computations are distributed. Th principally by matchinglaser scans to decrease localizationetechniques have been tested extensively in real-world trial error. The central m

apper further improves the mapsand simulations. The results demonstrate th (minimizing localization error) by iteratively combininge performanceimp data from the robots. This works under the assumption thatrovements and robustness that accrue from our multi-robot approach to expl the robots know their pose relative to one another and haveoration.

access to high-bandwidth communication.

1 Introduction Similarly, our approach to coordinating explorationcombines distributed computation with global decision

Creating maps of the environment is a fundamental making. The individual robotsconstruct bids, whichchallenge in mobile robotics. In general, to do so efficiently describe their estimates of the expected information gainrequires good exploration strategies. In particular, the and costs of travelingto various locations. A centralrobots need to know what areas are worthwhile to explore executive receives thebids and assigns tasks in an attemptand how to distribute themselves effectively in to maximize overall utility, while trying to minimize order to


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thoroughly map previously unknown areas. overlap in coverage by the robots. In both cases, the

Most previous work in mapping dealt only with singl majority of the computationis done in a distributederob fashion, by the individual robots, and the centralizedots. There are, however, advantages in mapping withmultiple robots. The most obvious is that multipl modules combine and coordinateinformation in ane robots efficient way.can often do the task in less time. This may not alwayshold, however, due to interference between robots [6, 8]. After presenting related work, Sections 3 and 4 describeThus, it is important for the exploration strategies to keep our approaches to multi-robot map creation andthe robots relatively well separated. Another advantage is exploration, respectively. Section 5 presents a case study ofthat multiple robots may produce more accurate maps, due three robots combiningto map a large indoor area. We alsoto merging of overlapping information. This can help analyze quantitative results from simulations showing thecompensate for sensor uncertainty and localization error, effects of our exploration strategies on task performance.especially where the robots have different sensor and/or Finally, we discuss future directions that are important to

localization capabilities [7]. the problems of multi-robot exploration and mapping.This paper presents techniques for coordinating multiple,heterogeneous robots in their task of exploring 2 Related Work andmapping large, indoor environments. We consider twocoordi While there has been work in mapping and exploration fornation problems creating a single global mapfrom the sensor information of the individual robots, and single robot systems [3, 4, 9, 17, 18], there have beendeciding relatively few approaches for mapping and exploration where each robotshould go in order to create themap most effectively. While solving the latter probl with multi-robot systems. Several researchers have studiedem the problem of using multiple robots to reduce

localizationCopyright 2000, American Association for Artificial Intelligence error during exploration [10, 13]. For instance, in Rekleitis(www.aaai.org). All rights reserved.}}

@InCollection{rybski2007communication, Title = {Communication strategies in multi-robot search andretrieval: Experiences with mindart}, Author = {Rybski, Paul E and Larson, Amy and Veeraraghavan,Harini and LaPoint, Monica and Gini, Maria}, Booktitle = {Distributed Autonomous Robotic Systems 6}, Publisher = {Springer},

Year = {2007}, Pages = {317--326},

__markedentry = {[Florian:]}, File = {:papers\\2007_Communication strategies in multi-robot search and retrieval Experiences with mindart.pdf:PDF}}

@Article{saffre1999collective, Title = {Collective decision-making in social spiders: drag


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line-mediated amplification process acts as a recruitment mechanism}, Author = {Saffre, Fabrice and Furey, Robert and Krafft, B and Deneubourg, Jean-Louis}, Journal = {Journal of Theoretical Biology}, Year = {1999}, Number = {4}, Pages = {507--517}, Volume = {198},

__markedentry = {[Florian:1]}, File = {:papers\\1999_Collective decision-making in socialspiders dragline-mediated amplification process acts as a recruitment mechanism.pdf:PDF}, Publisher = {Elsevier}}

@Article{trianni2006self, Title = {Self-organisation and communication in groups of simulated and physical robots}, Author = {Trianni, Vito and Dorigo, Marco}, Journal = {Biological cybernetics}, Year = {2006}, Number = {3}, Pages = {213--231},

Volume = {95},

__markedentry = {[Florian:4]}, File = {:papers\\2006_Self-organisation and communicationin groups of simulated and physical robots.pdf:PDF}, Publisher = {Springer}}

@InProceedings{trianni2005emergent, Title = {Emergent collective decisions in a swarm of robots}, Author = {Trianni, Vito and Dorigo, Marco}, Booktitle = {Swarm Intelligence Symposium, 2005. SIS 2005. Proc

eedings 2005 IEEE}, Year = {2005}, Organization = {IEEE}, Pages = {241--248},

__markedentry = {[Florian:1]}, File = {:papers\\2005_Evolving communicating agents that integrate information over time a real robot experiment.pdf:PDF}}

@InProceedings{Trianni2004, Title = {Evolution of Direct Communication for a Swarm-botPerforming Hole Avoidance},

Author = {Vito Trianni and Thomas H. Labella and Marco Dorigo}, Booktitle = {ANTS 2004}, Year = {2004}, Editor = {M. Dorigo and others}, Pages = {130141}, Publisher = {Springer}, Series = {LNCS}, Volume = {3172},


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__markedentry = {[Florian:]}, Abstract = {Communication is often required for coordination of collec-tive behaviours. Social insects like ants, termites or bees make use of dif-ferent forms of communication, which can be roughly classied in threeclasses: indirect (stigmergic) communication, direct interaction and di-rect communication. The use of stigmergic communication is predomi-nant in social insects (e.g., the pheromone trails in ants), but also directinteractions (e.g., antennation in ants) and direct communication can beobserved (e.g., the waggle dance of honey bee workers). Direct communi-cation may be benecial when a fast reaction is expected, as for instance,when a danger is detected and countermeasures must be taken. This isthe case of hole avoidance, the task studied in this paper: a group of self-assembled robots called swarm-bot coordinately explores an arenacontaining holes, avoiding to fall into them. In particular, we study theuse of direct communication in order to achieve a reaction to the detec-tion of a hole faster than with the sole use of direct interactions throughphysical links. We rely on articial evolution for the synthesis of neuralnetwork controllers, showing that evolving behaviours that make use ofdirect communication is more eective than exploiting direct interactionsonly.}, File = {:papers\\2004_Evolution of Direct Communication for a Swarm-bot Performing Hole Avoidance.pdf:PDF}, Keywords = {evolutionary robotics, swarm robotics, communicati

on}, Review = {Evolution of Direct Communicationfor a Swarm-bot Performing Hole Avoidance

Vito Trianni, Thomas H. Labella, and Marco Dorigo

IRIDIA - Universite Libre de Bruxelles - Brussels, Belgium{vtrianni,hlabella,mdorigo}@ulb.ac.be

Abstract. Communication is often required for coordination of collec-tive behaviours. Social insects like ants, termites or bees make use of dif-ferent forms of communication, which can be roughly classied in threeclasses: indirect (stigmergic) communication, direct interaction and di-

rect communication. The use of stigmergic communication is predomi-nant in social insects (e.g., the pheromone trails in ants), but also directinteractions (e.g., antennation in ants) and direct communication can beobserved (e.g., the waggle dance of honey bee workers). Direct communi-cation may be benecial when a fast reaction is expected, as for instance,when a danger is detected and countermeasures must be taken. This isthe case of hole avoidance, the task studied in this paper: a group of self-assembled robots called swarm-bot coordinately explores an arenacontaining holes, avoiding to fall into them. In particular, we study theuse of direct communication in order to achieve a reaction to the detec-tion of a hole faster than with the sole use of direct interactions throughphysical links. We rely on articial evolution for the synthesis of neuralnetwork controllers, showing that evolving behaviours that make use of

direct communication is more eective than exploiting direct interactionsonly.

Keywords: evolutionary robotics, swarm robotics, communication.

1 Introduction

In collective robotics research, the coordination of the activities in a group ofrobots requires the denition of communication strategies and protocols among


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the individuals. These strategies and protocols need not, however, be particu-larly complex. In many cases, simple forms of communication or no explicitcommunication at all are enough to obtain the coordination of the activitiesof the group [11]. This is the case of swarm robotics, that, drawing inspirationfrom social insects such as ants, termites or bees, focuses on distributed roboticsystems characterised by limited communication abilities among robots.

Communication in social insects has been thoroughly studied, identifyingdierent modalities used for the regulation of the colony's activities. The studyof the nest building behaviour of termites of the genus Macrotermes led Grasseto the introduction of the concept of stigmergy [9]. Impressed by the complexityof termites' nests and by their dimension with respect to an individual, Grasse

M. Dorigo et al. (Eds.): ANTS 2004, LNCS 3172, pp. 130141, 2004.c Springer-Verlag Berlin Heidelberg 2004}}

@InProceedings{watson2002embodied, Title = {Embodied evolution: Distributing an evolutionary algorithm in a population of robots}, Author = {Watson, Richard A and Ficici, Sevan G and Pollack,Jordan B}, Year = {2002},

Number = {1}, Pages = {1--18}, Publisher = {Elsevier}, Volume = {39},

__markedentry = {[Florian:]}, File = {:papers\\2002_Embodied Evolution (Watson).pdf:PDF}, Journal = {Robotics and Autonomous Systems}, Keywords = {Evolutionary robotics; Artificial Life; Evolutionary algorithms; Distributed learning; Collective robotics}, Review = {Robotics and Autonomous Systems 39 (2002) 118

Embodied Evolution:Distributing an evolutionary algorithm

in a population of robotsRichard A. Watson, Sevan G. Ficici, Jordan B. Pollack

Dynamical and Evolutionary Machine Organization, Volen National Center for Complex Systems,Brandeis University, Waltham, MA 02454, USA

Received 3 June 2000; received in revised form 10 May 2001Communicated by T.C. Henderson

Abstract

We introduce Embodied Evolution (EE) as a new methodology for evolutionary robotics (ER). EE uses a population ofphysical robots that autonomously reproduce with one another while situated in their task environment. This constitutes afully distributed evolutionary algorithm embodied in physical robots. Several issues identified by researchers in the evolu-tionary robotics community as problematic for the development of ER are alleviated by the use of a large number of robots


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being evaluated in parallel. Particularly, EE avoids the pitfalls of the simulate-and-transfer method and allows the speed-upof evaluation time by utilizing parallelism. The more novel features of EE are that the evolutionary algorithm is entirelydecentralized, which makes it inherently scalable to large numbers of robots, and that it uses many robots in a shared taskenvironment, which makes it an interesting platform for future work in collective robotics and Artificial Life. We have builta population of eight robots and successfully implemented the first example of Embodied Evolution by designing a fullydecentralized, asynchronous evolutionary algorithm. Controllers evolved by EE outperform a hand-designed controller in asimple application. We introduce our approach and its motivations, detail our implementation and initial results, and discussthe advantages and limitations of EE. 2002 Elsevier Science B.V. All rights reserved.

Keywords: Evolutionary robotics; Artificial Life; Evolutionary algorithms; Distributed learning; Collective robotics

1. Introduction exchange genetic material, producing `offspring' con-trol programs that become resident in other members

1.1. Vision of the robot population. Naturally, the likelihood of

a robot producing offspring is regulated by its ability

Our work is inspired by the following vision. A to perform the task or collect `energy'. Further, therelarge number of robots freely interact with each other is no need for human intervention either to evaluate,in a shared environment, attempting to perform some breed, or reposition the robots for new trials.tasksay the collection of objects representing food This vision, to our knowledgefirst described byor energy Husbands et al. [1], aspires to an ideal where the robot. The robots mate with each other, i.e.,

population evolves in a completely hands-free andCorresponding author autonomous manner; in so doing, it offers intriguing.

E-mail address: [email protected] (R.A. Watson). possibilities for the future of evolutionary robotics

0921-8890/02/$ see front matter 2002 Elsevier Science B.V. All rights reserved.PII: S0 9 2 1 -8890 (02 )00170 -7}}

@InProceedings{werner1997too, Title = {Too many love songs: Sexual selection and the evolution of communication},

Author = {Werner, Gregory M and Todd, Peter M}, Booktitle = {Fourth European Conference on Artificial Life}, Year = {1997}, Organization = {MIT Press}, Pages = {434--443},

__markedentry = {[Florian:1]}, File = {:papers\\1997_Too many love songs Sexual selectionand the evolution of communication.pdf:PDF}}


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