SPECIAL ISSUE

New Trends in Swarm Robotics

Dear Colleagues,

We are inviting submissions to a Special Issue on New Trends in Swarm Robotics.

We invite submissions exploring cutting-edge research and recent advances in swarm robotics which include, but are not limited to, the following topics: surveillance systems, distributed systems, modelling and simulation, cooperative control, swarm intelligence, swarms of drones, multi-agent systems, self-organisation, robot formation control, distributed machine learning, collective mapping, and UAV traffic management (UTM).

Both theoretical and experimental studies are welcome, as well as comprehensive review and survey papers. We look forward to receiving submissions of your quality research work.

Dr. Daniel H. Stolfi
Dr. Grégoire Danoy
Guest Editor

FEATURED CONTENTS

Flow Generator Algorithm (FGA)

We present a novel approach for calculating realistic traffic flows for traffic simulators, called Flow Generator Algorithm (FGA). We start with an original map from OpenStreetMap and traffic data collected at different measurement points, published by the city’s authorities, to produce a model consisting of the simulation map and a series of traffic flows (routes + vehicles) which match the real number of vehicles at those streets. Our approach does not need a full dataset to calculate the flows. In fact, just a few measurement points indicating the number of vehicles in the analyzed time interval were used. This and the use of evolutionary algorithms for such a complex task make our proposal different from the studies found in literature.

The epiGenetic Algorithm (epiGA)

Our novel proposal, the epiGenetic Algorithm (epiGA), consists of a set of strategies, based on evolutionary computation, inspired in nature, especially in epigenetics, with the aim of solving complex combinatorial problems. The foundation of epiGA is epigenesis. We are interested in how the DNA and histones are collapsed to form nucleosomes, how this affects the gene replication during reproduction, and how the epigenetic mechanisms modify the gene expression thru methylation, all of them in order to build the bio-inspired operators of our algorithm. Source code in GitLab: JAVA and Python

Green Swarm: Reducing Greenhouse Gas Emissions

The mobility architecture, called Green Swarm, is proposed to reduce greenhouse gas emissions from road traffic in smart cities. The traffic flow optimization of four European cities: Malaga, Stockholm, Berlin, and Paris, is addressed with new case studies importing each city's actual roads and traffic lights from OpenStreetMap into the SUMO traffic simulator, so as to find the best ways to redirect the traffic flow, and advise drivers.

Red Swarm: Smart Mobility in Smart Cities

Nowadays, cities are evolving quickly. Most citizens are living in, using the services of, or thinking about moving to cities, what is a new source of complex problems. Smart Cities is a world initiative leading to better exploit on of the resources in a city in order to offer higher level services to people. Smart cities are related to sensing the city's status and acting in new intelligent ways at different levels: people, government, cars, transport, communications, energy, buildings, neighbourhoods, resource storage, etc.

Project CoMVeT (AKA SUMBUDRULE)

The Emotiv EPOC neuroheadset is used to register neural activity with high resolution. This activity is processed and sent to the computer using a wireless link. This neuroheadset represents a new type of interface human-machine (HCI) and it's able to interpret signals from the user's brain. This neuroheadset has several wet pads used like electrodes to detect the user's basic thoughts, feelings, emotions and facial gestures.

Vertical pendulum: Control by computer

Development of a proportional-derivative controller used to keep a pendulum in vertical position. It has got only one degree of freedom corresponding to the tilt angle. The mechanical structure has been built by using the rail and the head of an old printer to mount the tilt sensor in order to close the loop of the control.

Building a slave flash trigger

This development consists in mounting a circuit for triggering a slave flash. These kind of devices are well known by photographers and they use to be very expensive. By using this trigger you will be capable to take photos with more than a flash at once.

MULTIMEDIA CONTENT

RESEARCH PROJECTS

The ADARS project (Automating the Design of Autonomous Robot Swarms) aims to propose a unique solution to the design of distributed autonomous systems by addressing the following question: is it possible to automatically generate efficient and reusable behaviors for distributed aerospace and space systems (DASS)? To this end, ADARS will advance the state-of-the-art in the field of swarm robotics and automated algorithm design. Read more...

The HUNTED project (Heterogeneous multi-swarms of UNmanned auTonomous systEms for mission Deployment) aims at designing a novel generation of mobility models for heterogeneous multi-swarms of Unmanned Autonomous Systems (UAS) for surveillance and tracking of imminent threats. Such swarms are composed of several vehicles moving in an autonomous and coordinated manner in the air, on the ground, and in the sea. Read more...

In the 6CITY project (TIN2017-88213-R) the working hypothesis is that many different problems of smart cities (according to EU: economy, mobility, governance, people, living, environment), which are multidisciplinary in nature and apparently unrelated, can be solved by looking at their (possibly similar) underlying quantitative and qualitative features, as well as by providing advanced algorithms that can search, optimize and learn by themselves (to an extent) for those situations where knowledge of the problem is very limited (as it happens in many real cases). Read more...

The MOVEON project (TIN2014-57341-R) makes an ambitious proposal for focused research in challenges related to intelligent transport and smart mobility. We do it from the perspective of building new applications based in solver metaheuristic engines enhanced with methodologies and theories contributed by our team so as to exhibit "holistic intelligence". Read more...

The MAXCT project (OTRI # 8.06/5.47.4356 - AOP GGI3003IDI) consists of two parallel applications are running to improve the traffic flow in a city: HITUL - Holistic Intelligence for Traffic Urban Lights - system offers an informed support for decision-making at city level, optimizing the planning of the existing traffic lights network; and CTPATH is our second tool in this project. Drivers could receive route advices based in their preferences and city conditions, both powered to reduce the travel times and the carbon footprint. Read more...

The roadME project (TIN2011-28194) intends to characterize, design, and evaluate metaheuristic techniques able to solve real world problems, and then, particular applications of a communication network of vehicles (VANET). Our hypothesis is that standard metaheuristics are not able by themselves to address the tight requirements of many complex problems like this one, since we are dealing with execution times of a few seconds, specific user constraints, scalable to very big dimension problems, and robust to work in different scenarios. Read more...

The Project PATIO: Collaborative Learning and User Modelling Techniques Applied to Multicultural Integration (TIC-4273), has been developed by the group of Investigation and Application of Artificial Intelligence of the department of Computer Languages and Computation of the University of Málaga, subsidized by the Ministry of Innovation, Science and Business of the Andalusian Regional Government (2008 official announcement for excellence Projects). Read more...

publications

Full List

SuSy-EnGaD: Surveillance System Enhanced by Games of Drones

Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, Pascal Bouvry. SuSy-EnGaD: Surveillance System Enhanced by Games of Drones. In: Drones, vol. 6, no. 1, Art. no. 13, 2022.
doi> 10.3390/drones6010013 | [BibTex]

@Article{drones6010013,
   author         = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Grégoire and Bouvry, Pascal},
   journal        = {Drones},
   title          = {SuSy-EnGaD: Surveillance System Enhanced by Games of Drones},
   year           = {2022},
   issn           = {2504-446X},
   number         = {1},
   volume         = {6},
   article-number = {13},
   doi            = {10.3390/drones6010013},
   url            = {https://www.mdpi.com/2504-446X/6/1/13},
}

A competitive Predator-Prey approach to enhance surveillance by UAV swarms

Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. A competitive Predator-Prey approach to enhance surveillance by UAV swarms. In: Applied Soft Computing, vol. 111, p. 107701, 2021.
doi> 10.1016/j.asoc.2021.107701 | [BibTex]

@article{Stolfi2021c,
   title = {A competitive Predator–Prey approach to enhance surveillance by UAV swarms},
   journal = {Applied Soft Computing},
   volume = {111},
   pages = {107701},
   year = {2021},
   issn = {1568-4946},
   doi = {https://doi.org/10.1016/j.asoc.2021.107701},
   url = {https://www.sciencedirect.com/science/article/pii/S1568494621006220},
   author = {Daniel H. Stolfi and Matthias R. Brust and Grégoire Danoy and Pascal Bouvry},
   keywords = {Swarm robotics, Computer simulation, Mobility model, Unmanned aerial vehicle, Competitive coevolutionary genetic algorithm},
}

Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga

Daniel H. Stolfi and Enrique Alba. Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga. In: Applied Soft Computing, vol. 109, p. 107566, 2021.
doi> 10.1016/j.asoc.2021.107566 | [BibTex]

@article{STOLFI2021107566,
   title = {Yellow Swarm: LED panels to advise optimal alternative tours to drivers in the city of Malaga},
   journal = {Applied Soft Computing},
   volume = {109},
   pages = {107566},
   year = {2021},
   issn = {1568-4946},
   doi = {https://doi.org/10.1016/j.asoc.2021.107566},
   url = {https://www.sciencedirect.com/science/article/pii/S1568494621004877},
   author = {Daniel H. Stolfi and Enrique Alba},
   keywords = {epiGenetic algorithm, Smart mobility, LED panel, Travel time, Greenhouse gas emissions, Fuel consumption}
}

CONSOLE: intruder detection using a UAV swarm and security rings

Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. CONSOLE: intruder detection using a UAV swarm and security rings. In: Swarm Intelligence, 15, 205–235, 2021.
doi> 10.1007/s11721-021-00193-7 | [BibTex]

@Article{Stolfi2021a,
   author    = {Daniel H. Stolfi and Matthias R. Brust and Gr{\'{e}}goire Danoy and Pascal Bouvry},
   journal   = {Swarm Intelligence},
   title     = {CONSOLE: intruder detection using a UAV swarm and security rings},
   year      = {2021},
   issn      = {1935-3820},
   number    = {3},
   pages     = {205--235},
   volume    = {15},
   doi       = {10.1007/s11721-021-00193-7},
   publisher = {Springer Science and Business Media {LLC}},
   refid     = {Stolfi2021},
   url       = {https://doi.org/10.1007/s11721-021-00193-7},
}

Swarm-based counter UAV defense system

Matthias R. Brust, Grégoire Danoy, Daniel H. Stolfi, Pascal Bouvry. Swarm-based counter UAV defense system. In: Discover Internet of Things, vol. 1, no. 1, 2021.
doi> 10.1007/s43926-021-00002-x | [BibTex]

@Article{Brust2021,
   author    = {Matthias R. Brust and Gr{\'{e}}goire Danoy and Daniel H. Stolfi and Pascal Bouvry},
   journal   = {Discover Internet of Things},
   title     = {Swarm-based counter {UAV} defense system},
   year      = {2021},
   month     = {feb},
   number    = {1},
   volume    = {1},
   doi       = {10.1007/s43926-021-00002-x},
   publisher = {Springer Science and Business Media {LLC}},
}

UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance

Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance. In: Frontiers in Robotics and AI, vol. 8, Feb. 2021.
doi> 10.3389/frobt.2021.616950 | [BibTex]

@article{Stolfi2021,
   author = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Gr{\'{e}}goire and Bouvry, Pascal},
   doi = {10.3389/frobt.2021.616950},
   issn = {2296-9144},
   journal = {Frontiers in Robotics and AI},
   month = {feb},
   title = {{UAV-UGV-UMV Multi-Swarms for Cooperative Surveillance}},
   url = {https://www.frontiersin.org/articles/10.3389/frobt.2021.616950/full},
   volume = {8},
   year = {2021}
}

Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques

Daniel H. Stolfi, Matthias R. Brust, Grégoire Danoy, and Pascal Bouvry. Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques. In: Sensors, vol. 20, no. 9, 2020.
doi> 10.3390/s20092566 | [BibTex]

@Article{s20092566,
   AUTHOR = {Stolfi, Daniel H. and Brust, Matthias R. and Danoy, Grégoire and Bouvry, Pascal},
   TITLE = {Emerging Inter-Swarm Collaboration for Surveillance Using Pheromones and Evolutionary Techniques},
   JOURNAL = {Sensors},
   VOLUME = {20},
   YEAR = {2020},
   NUMBER = {9},
   ARTICLE-NUMBER = {2566},
   URL = {https://www.mdpi.com/1424-8220/20/9/2566},
   ISSN = {1424-8220},
   DOI = {10.3390/s20092566}
}

Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities

Daniel H. Stolfi, Enrique Alba, and Xin Yao. Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities. In: Journal of Urban Technology, 27:4, 27-41, 2020.
doi> 10.1080/10630732.2019.1586223 | [BibTex]

@article{doi:10.1080/10630732.2019.1586223,
   author = {Daniel H. Stolfi and Enrique Alba and Xin Yao},
   title = {Can I Park in the City Center? Predicting Car Park Occupancy Rates in Smart Cities},
   journal = {Journal of Urban Technology},
   volume = {27},
   number = {4},
   pages = {27-41},
   year  = {2020},
   publisher = {Routledge},
   doi = {10.1080/10630732.2019.1586223},
   URL = {https://doi.org/10.1080/10630732.2019.1586223},
   eprint = {https://doi.org/10.1080/10630732.2019.1586223}
}

Chapter 14 - Sustainable Road Traffic Using Evolutionary Algorithms

Daniel H. Stolfi and Enrique Alba. Chapter 14 - Sustainable Road Traffic Using Evolutionary Algorithms. In: Sustainable Transportation and Smart Logistics, Elsevier, 361-380, Eds: Faulin, Javier, Grasman, Scott E., Juan, Angel A., Hirsch, Patrick, 2019.
doi> 10.1016/B978-0-12-814242-4.00014-4 | [BibTex]

@incollection{STOLFI2019361,
   title = "Chapter 14 - Sustainable Road Traffic Using Evolutionary Algorithms",
   editor = "Javier Faulin and Scott E. Grasman and Angel A. Juan and Patrick Hirsch",
   booktitle = "Sustainable Transportation and Smart Logistics",
   publisher = "Elsevier",
   pages = "361 - 380",
   year = "2019",
   isbn = "978-0-12-814242-4",
   doi = "https://doi.org/10.1016/B978-0-12-814242-4.00014-4",
   url = "http://www.sciencedirect.com/science/article/pii/B9780128142424000144",
   author = "Daniel H. Stolfi and Enrique Alba",
   keywords = "Evolutionary algorithm, Intelligent transportation systems, LED panels, Road traffic, Smart mobility, Wi-Fi connections"
}

Green Swarm: Greener Routes with Bio-inspired Techniques

Daniel H. Stolfi and Enrique Alba. Green Swarm: Greener Routes with Bio-inspired Techniques. In: Applied Soft Computing, vol. 71, pp. 952-963, 2018.
doi> 10.1016/j.asoc.2018.07.032 | [BibTex] | Read More...

@article{STOLFI2018952,
   author = {Daniel H. Stolfi and Enrique Alba},
   doi = {10.1016/j.asoc.2018.07.032},
   issn = {1568-4946},
   journal = {Applied Soft Computing},
   keywords = {Evolutionary algorithm; Road traffic; Smart city; Smart mobility; Gas emissions; Wi-Fi connections},
   pages = {952--963},
   title = {{Green Swarm: Greener routes with bio-inspired techniques}},
   url = {http://www.sciencedirect.com/science/article/pii/S1568494618304204},
   volume = {71},
   year = {2018}
}

Generating Realistic Urban Traffic Flows with Evolutionary Techniques

Daniel H. Stolfi and Enrique Alba. Generating Realistic Urban Traffic Flows with Evolutionary Techniques. In: Engineering Applications of Artificial Intelligence, vol. 75, pp. 36-47, 2018.
doi> 10.1016/j.engappai.2018.07.009 | [BibTex] | Read More...

@article{STOLFI201836,
   title = "Generating realistic urban traffic flows with evolutionary techniques",
   journal = "Engineering Applications of Artificial Intelligence",
   volume = "75",
   pages = "36 - 47",
   year = "2018",
   issn = "0952-1976",
   doi = "https://doi.org/10.1016/j.engappai.2018.07.009",
   url = "http://www.sciencedirect.com/science/article/pii/S0952197618301532",
   author = "Daniel H. Stolfi and Enrique Alba",
   keywords = "Evolutionary algorithm, Traffic simulation, Smart mobility, SUMO, Road traffic optimization, O–D matrix"
}

Epigenetic algorithms: A New way of building GAs based on epigenetics

Daniel H. Stolfi and Enrique Alba. Epigenetic algorithms: A New way of building GAs based on epigenetics. In: Information Sciences, vol. 424, Supplement C, pp. 250-272, 2018.
doi> 10.1016/j.ins.2017.10.005 | [BibTex] | Read More...

@article{STOLFI2018250,
   author = "Stolfi, Daniel H. and Alba, Enrique",
   doi = "10.1016/j.ins.2017.10.005",
   issn = "0020-0255",
   journal = "Information Sciences",
   keywords = "Evolutionary algorithm; Epigenetics; MKP; Bio-inspiration",
   number = "Supplement C",
   pages = "250--272",
   title = "{Epigenetic algorithms: A New way of building GAs based on epigenetics}",
   url = "http://www.sciencedirect.com/science/article/pii/S0020025517309921",
   volume = "424",
   year = "2018"
}

Red Swarm: Reducing Travel Times in Smart Cities by Using Bio-inspired Algorithms

Daniel H. Stolfi and Enrique Alba. Red Swarm: Reducing Travel Times in Smart Cities by Using Bio-inspired Algorithms. In: Applied Soft Computing, vol. 24, pp. 181-195, 2014.
doi> 10.1016/j.asoc.2014.07.014 | [BibTex] | Read More...

@article{STOLFI2014181,
   title = "Red Swarm: Reducing travel times in smart cities by using bio-inspired algorithms",
   journal = "Applied Soft Computing",
   volume = "24",
   pages = "181 - 195",
   year = "2014",
   issn = "1568-4946",
   doi = "https://doi.org/10.1016/j.asoc.2014.07.014",
   url = "http://www.sciencedirect.com/science/article/pii/S1568494614003457",
   author = "Daniel H. Stolfi and Enrique Alba",
   keywords = "Evolutionary algorithm, Road traffic, Smart city, Smart mobility, WiFi connections, Traffic light"
}

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