Comparación empírica de métodos de diseño de enjambres de robots: un estudio en simulación sobre enjambres que coordinan a otros enjambres.
dc.rights.license | Reconocimiento 4.0 Internacional |
dc.contributor.advisor | Vargas-Hernandez, Carlos |
dc.contributor.author | Garzón Ramos, David |
dc.date.accessioned | 2022-03-24T19:53:13Z |
dc.date.available | 2022-03-24T19:53:13Z |
dc.date.issued | 2022 |
dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/81376 |
dc.description | ilustraciones, tablas. |
dc.description.abstract | Esta tesis presenta una comparación empírica de métodos de diseño de comportamientos colectivos para enjambres de robots que deben coordinar a otros enjambres. En este estudio, los métodos de diseño producen software de control sin ser provistos con información explícita sobre el comportamiento de los enjambres que deben ser coordinados—esta información debe ser obtenida durante el proceso de diseño. Los métodos considerados en la comparación son Pistacchio, EvoCMY, C-Human, R-Walk. Pistacchio es un método automático modular, perteneciente a la familia de métodos AutoMoDe. EvoCMY es un método automático basado en neuroevolución. La eficiencia de los métodos automáticos fue comparada con C-Human, un método de diseño manual en donde un grupo de diseñadores producen el software de control para los robots. Pistacchio, EvoCMY y C-Human fueron comparados con R-Walk, una implementación de movimiento aleatorio que sirve como línea base. Pistacchio y EvoCMY se presentan por primera vez en esta tesis, y son una contribución de la investigación. Los experimentos llevados a cabo con Pistacchio y EvoCMY permitieron determinar que los métodos de diseño automático son efectivos en (i) la identificación de posibles formas de interacción entre el enjambre que coordina y el enjambre que es coordinado; y en (ii) el aprovechamiento de estas formas de interacción para ejecutar misiones en donde los dos enjambres operan de forma coordinada. La comparación de los métodos se llevó a cabo empleando ARGoS3, un simulador especializado en robótica de enjambres, y tomando como plataforma de referencia al robot e-puck. El diseño mediante métodos automáticos resultó significativamente más eficiente que el diseño manual en las misiones propuestas. |
dc.description.abstract | This thesis presents an empirical comparison of methods for the design of collective behaviors for a robot swarm that must coordinate a second robot swarm. In this study, the design methods produce control software without being provided with explicit information about the behavior of the swarm that must be coordinated—in all cases, this information must be obtained during the design process. The methods considered in the study are Pistacchio, EvoCMY, C-Human, R-Walk. Pistacchio is an automatic modular method that belongs to the family of methods AutoMoDe. EvoCMY is an automatic method based on neuro-evolution. The performance of the automatic methods was compared with the performance of C-Human, a manual design method in which a group of human designers produces the control software for the robots. Pistacchio, EvoCMY and C-Human were compared against R-Walk, an implementation of a random walk that serves as a baseline. Pistacchio and EvoCMY are presented for the first time in this thesis, and they are an original contribution. Experiments conducted with Pistacchio and EvoCMY showed that automatic design methods are effective in (i) identifying interaction dynamics between the swarm that coordinates and the swarm that is being coordinated; and in (ii) using these dynamics for addressing missions in which the two robot swarms must act in a coordinated manner. The design methods were compared in simulation, using the swarm-dedicated simulator ARGoS3 and a simulated model of the e-puck robot. The automatic design approach performed significantly better than the manual design in the proposed missions. |
dc.format.extent | xv, 85 páginas |
dc.format.mimetype | application/pdf |
dc.language.iso | spa |
dc.publisher | Universidad Nacional de Colombia |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ |
dc.subject.ddc | 620 - Ingeniería y operaciones afines::629 - Otras ramas de la ingeniería |
dc.title | Comparación empírica de métodos de diseño de enjambres de robots: un estudio en simulación sobre enjambres que coordinan a otros enjambres. |
dc.type | Trabajo de grado - Maestría |
dc.type.driver | info:eu-repo/semantics/masterThesis |
dc.type.version | info:eu-repo/semantics/acceptedVersion |
dc.publisher.program | Manizales - Ingeniería y Arquitectura - Maestría en Ingeniería - Automatización Industrial |
dc.description.degreelevel | Maestría |
dc.description.degreename | Magíster en Ingeniería - Automatización Industrial |
dc.description.researcharea | Diseño de comportamientos colectivos para enjambres de robots |
dc.identifier.instname | Universidad Nacional de Colombia |
dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia |
dc.identifier.repourl | https://repositorio.unal.edu.co/ |
dc.publisher.department | Departamento de Ingeniería Eléctrica y Electrónica |
dc.publisher.faculty | Facultad de Ingeniería y Arquitectura |
dc.publisher.place | Manizales, Colombia |
dc.publisher.branch | Universidad Nacional de Colombia - Sede Manizales |
dc.relation.references | Gerardo Beni. From swarm intelligence to swarm robotics. In Erol Şahin y William M. Spears, editors, Swarm Robotics: SAB 2004 International Workshop, volume 3342 of Lecture Notes in Computer Science, pages 1–9, Berlin, Germany, 2005. Springer. doi: 10.1007/978-3-540-30552-1_1. |
dc.relation.references | Erol Şahin. Swarm robotics: from sources of inspiration to domains of application. In Erol Şahin y William M. Spears, editors, Swarm Robotics: SAB 2004 International Workshop, volume 3342 of Lecture Notes in Computer Science, pages 10–20, Berlin, Germany, 2005. Springer. doi: 10.1007/978-3-540-30552-1_2. |
dc.relation.references | Marco Dorigo, Mauro Birattari, y Manuele Brambilla. Swarm robotics. Scholarpedia, 9 (1):1463, 2014. doi: 10.4249/scholarpedia.1463. |
dc.relation.references | Manuele Brambilla, Eliseo Ferrante, Mauro Birattari, y Marco Dorigo. Swarm robotics: a review from the swarm engineering perspective. Swarm Intelligence, 7(1):1–41, 2013. doi: 10.1007/s11721-012-0075-2. |
dc.relation.references | Marco Dorigo, Guy Theraulaz, y Vito Trianni. Reflections on the future of swarm robotics. Science Robotics, 5:eabe4385, 2020. doi: 10.1126/scirobotics.abe4385 |
dc.relation.references | Marco Dorigo, Guy Theraulaz, y Vito Trianni. Swarm robotics: past, present, and future. Proceedings of the IEEE, 109(7):1152–1165, 2021. doi: 10.1109/JPROC.2021.3072740. |
dc.relation.references | Marco Dorigo, Guy Theraulaz, y Vito Trianni. Swarm robotics: past, present, and future [point of view]. Proceedings of the IEEE, 109(7):1152–1165, 2021. doi: 10.1109/JPROC.2021.3072740. |
dc.relation.references | Gianpiero Francesca y Mauro Birattari. Automatic design of robot swarms: achievements and challenges. Frontiers in Robotics and AI, 3(29):1–9, 2016. doi: 10.3389/frobt.2016.00029. |
dc.relation.references | Mauro Birattari, Antoine Ligot, Darko Bozhinoski, Manuele Brambilla, Gianpiero Francesca, Lorenzo Garattoni, David Garzón Ramos, Ken Hasselmann, Miquel Kegeleirs, Jonas Kuckling, Federico Pagnozzi, Andrea Roli, Muhammad Salman, y Thomas Stützle. Automatic off-line design of robot swarms: a manifesto. Frontiers in Robotics and AI, 6:59, 2019. doi: 10.3389/frobt.2019.00059. |
dc.relation.references | Mauro Birattari, Antoine Ligot, y Ken Hasselmann. Disentangling automatic and semi-automatic approaches to the optimization-based design of control software for robot swarms. Nature Machine Intelligence, 2(9):494–499, 2020. doi: 10.1038/s42256-020-0215-0. |
dc.relation.references | Mauro Birattari, Antoine Ligot, y Gianpiero Francesca. AutoMoDe: a modular approach to the automatic off-line design and fine-tuning of control software for robot swarms. In Nelishia Pillay y Rong Qu, editors, Automated Design of Machine Learning and Search Algorithms, Natural Computing Series, pages 73–90. Springer, Cham, Switzerland, 2021. doi: 10.1007/978-3-030-72069-8_5. |
dc.relation.references | Ken Hasselmann, Antoine Ligot, Julian Ruddick, y Mauro Birattari. Empirical assessment and comparison of neuro-evolutionary methods for the automatic off-line design of robot swarms. Nature Communications, 12:4345, 2021. doi: 10.1038/s41467-021-24642-3. |
dc.relation.references | David Garzón Ramos y Mauro Birattari. Automatic design of collective behaviors for robots that can display and perceive colors. Applied Sciences, 10(13):4654, 2020. doi: 10.3390/app10134654. |
dc.relation.references | Ken Hasselmann y Mauro Birattari. Modular automatic design of collective behaviors for robots endowed with local communication capabilities. PeerJ Computer Science, 6:e291, 2020. doi: 10.7717/peerj-cs.291. |
dc.relation.references | Muhammad Salman, Antoine Ligot, y Mauro Birattari. Concurrent design of control software and configuration of hardware for robot swarms under economic constraints. PeerJ Computer Science, 5:e221, 2019. doi: 10.7717/peerj-cs.221. |
dc.relation.references | Antoine Ligot, Jonas Kuckling, Darko Bozhinoski, y Mauro Birattari. Automatic modular design of robot swarms using behavior trees as a control architecture. PeerJComputer Science, 6:e314, 2020. doi: 10.7717/peerj-cs.314. |
dc.relation.references | Jonas Kuckling, Thomas Stützle, y Mauro Birattari. Iterative improvement in the automatic modular design of robot swarms. PeerJ Computer Science, 6:e322, 2020. doi: 10.7717/peerj-cs.322. |
dc.relation.references | Jonas Kuckling, Keneth Ubeda Arriaza, y Mauro Birattari. AutoMoDe-IcePop: automatic modular design of control software for robot swarms using simulated annealing. In Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, y Gilles Louppe, editors, Artificial Intelligence and Machine Learning: BNAIC 2019, BENELEARN 2019, volume 1196 of Communications in Computer and Information Science, pages 3–17. Springer, Cham, Switzerland, 2020. |
dc.relation.references | Gianpiero Francesca, Manuele Brambilla, Arne Brutschy, Lorenzo Garattoni, Roman Miletitch, Gaëtan Podevijn, Andreagiovanni Reina, Touraj Soleymani, Mattia Salvaro, Carlo Pinciroli, Vito Trianni, y Mauro Birattari. An experiment in automatic design of robot swarms: AutoMoDe-Vanilla, EvoStick, and human experts. In Marco Dorigo, Mauro Birattari, Simon Garnier, Heiko Hamann, Marco Montes de Oca, Christine Solnon, y Thomas Stützle, editors, Swarm Intelligence: 9th International Conference, ANTS 2014, volume 8667 of Lecture Notes in Computer Science, pages 25–37, Cham, Switzerland, 2014. Springer International Publishing. doi: 10.1007/978-3-319-09952-1_3. |
dc.relation.references | Gianpiero Francesca, Manuele Brambilla, Arne Brutschy, Lorenzo Garattoni, Roman Miletitch, Gaëtan Podevijn, Andreagiovanni Reina, Touraj Soleymani, Mattia Salvaro, Carlo Pinciroli, Franco Mascia, Vito Trianni, y Mauro Birattari. AutoMoDe-Chocolate: automatic design of control software for robot swarms. Swarm Intelligence, 9(2–3): 125–152, 2015. doi: 10.1007/s11721-015-0107-9. |
dc.relation.references | Jonas Kuckling, Vincent Van Pelt, y Mauro Birattari. Automatic modular design of behavior trees for robot swarms with communication capabilities. In Pedro A. Castillo y Juan Luis Jiménez Laredo, editors, Applications of Evolutionary Computation: 24th International Conference, EvoApplications 2021, volume 12694 of Lecture Notes in Computer Science, pages 130–145, Cham, Switzerland, 2021. Springer. doi: 10.1007/978-3-030-72699-7_9. |
dc.relation.references | Gianpiero Francesca, Manuele Brambilla, Arne Brutschy, Vito Trianni, y Mauro Birattari. AutoMoDe: a novel approach to the automatic design of control software for robot swarms. Swarm Intelligence, 8(2):89–112, 2014. doi: 10.1007/s11721-014-0092-4. |
dc.relation.references | Vito Trianni. Evolutionary Swarm Robotics. Springer, Berlin, Germany, 2008. doi: 10.1007/978-3-540-77612-3. |
dc.relation.references | Carlo Pinciroli, Vito Trianni, Rehan O’Grady, Giovanni Pini, Arne Brutschy, Manuele Brambilla, Nithin Mathews, Eliseo Ferrante, Gianni A. Di Caro, Frederick Ducatelle, Mauro Birattari, Luca Maria Gambardella, y Marco Dorigo. ARGoS: a modular, parallel, multi-engine simulator for multi-robot systems. Swarm Intelligence, 6(4):271–295, 2012. doi: 10.1007/s11721-012-0072-5. |
dc.relation.references | Francesco Mondada, Michael Bonani, Xavier Raemy, Jim Pugh, Christopher Cianci, Adam Klaptocz, Stéphane Magnenat, Jean-Christophe Zufferey, Dario Floreano, y Alcherio Martinoli. The e-puck, a robot designed for education in engineering. In Paulo Gonçalves, Paulo Torres, y Carlos Alves, editors, ROBOTICA 2009: Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions, pages 59–65, Castelo Branco, Portugal, 2009. Instituto Politécnico de Castelo Branco. |
dc.relation.references | Guang-Zhong Yang, Jim Bellingham, Pierre E. Dupont, Peer Fischer, Luciano Floridi, Robert Full, Neil Jacobstein, Vijay Kumar, Marcia McNutt, Robert Merrifield, Bradley J. Nelson, Brian Scassellati, Mariarosaria Taddeo, Russell Taylor, Manuela Veloso, Zhong Lin Wang, y Robert Wood. The grand challenges of Science Robotics. Science Robotics, 3(14):eaar7650, 2018. doi: 10.1126/scirobotics.aar7650. |
dc.relation.references | Mauro Birattari. Tuning Metaheuristics: A Machine Learning Perspective. Springer, Berlin, Germany, 2009. doi: 10.1007/978-3-642-00483-4. |
dc.relation.references | David Garzón Ramos, Darko Bozhinoski, Gianpiero Francesca, Lorenzo Garattoni, Ken Hasselmann, Miquel Kegeleirs, Jonas Kuckling, Antoine Ligot, Fernando J. Mendiburu, Federico Pagnozzi, Muhammad Salman, Thomas Stützle, y Mauro Birattari. The automatic off-line design of robot swarms: recent advances and perspectives. In GiuliaDe Masi, Eliseo Ferrante, y Paolo Dario, editors, R2T2: Robotics Research for Tomorrow’s Technology, 2021. |
dc.relation.references | Nadia Nedjah y Luneque Silva Junior. Review of methodologies and tasks in swarm robotics towards standardization. Swarm and Evolutionary Computation, 50:100565, 2019. doi: 10.1016/j.swevo.2019.100565. |
dc.relation.references | Nithin Mathews, Anders Lyhne Christensen, Rehan O’Grady, Francesco Mondada, y Marco Dorigo. Mergeable nervous systems for robots. Nature Communications, 8(1):439, 2017. doi: 10.1038/s41467-017-00109-2. |
dc.relation.references | Marco Dorigo, Dario Floreano, Luca Maria Gambardella, Francesco Mondada, Stefano Nolfi, Tarek Baaboura, Mauro Birattari, Michael Bonani, Manuele Brambilla, Arne Brutschy, Daniel Burnier, Alexandre Campo, Anders Lyhne Christensen, Antal Decugnière, Gianni A. Di Caro, Frederick Ducatelle, Eliseo Ferrante, Alexander Förster, Javier Martinez Gonzales, Jérôme Guzzi, Valentin Longchamp, Stéphane Magnenat, Nithin Mathews, Marco Montes de Oca, Rehan O’Grady, Carlo Pinciroli, Giovanni Pini, Philippe Retornaz, James Roberts, Valerio Sperati, Timothy Stirling, Alessandro Stranieri, Thomas Stützle, Vito Trianni, Elio Tuci, Ali Emre Turgut, y Florian Vaussard. Swarmanoid: a novel concept for the study of heterogeneous robotic swarms. IEEE Robotics & Automation Magazine, 20(4):60–71, 2013. doi: 10.1109/MRA.2013.2252996. |
dc.relation.references | Lorenzo Garattoni y Mauro Birattari. Autonomous task sequencing in a robot swarm. Science Robotics, 3(20):eaat0430, 2018. doi: 10.1126/scirobotics.aat0430.76. |
dc.relation.references | Heiko Hamann. Swarm robotics: a formal approach. Springer, Cham, Switzerland, 2018. ISBN 978-3-319-74526-8. doi: 10.1007/978-3-319-74528-2. |
dc.relation.references | Melanie Schranz, Martina Umlauft, Micha Sende, y Wilfried Elmenreich. Swarm robotic behaviors and current applications. Frontiers in Robotics and AI, 7:36, 2020. doi: 10.3389/frobt.2020.00036. |
dc.relation.references | Lorenzo Garattoni y Mauro Birattari. Swarm robotics. In John G. Webster, editor, Wiley Encyclopedia of Electrical and Electronics Engineering, pages 1–19. John Wiley & Sons, Hoboken, NJ, USA, 2016. doi: 10.1002/047134608X.W8312. |
dc.relation.references | Marco Dorigo y Mauro Birattari. Swarm intelligence. Scholarpedia, 2(9):1462, 2007. doi: 10.4249/scholarpedia.1462. |
dc.relation.references | Edmund R. Hunt y Sabine Hauert. A checklist for safe robot swarms. Nature Machine Intelligence, 2:420–422, 2020. doi: 10.1038/s42256-020-0213-2. |
dc.relation.references | Heiko Hamann. Towards swarm calculus: universal properties of swarm performance and collective decisions. In Mauro Birattari, Christian Blum, Anders Lyhne Christensen, Andries P. Engelbrecht, Roderich Groß, Marco Dorigo, y Thomas Stützle, editors, Swarm Intelligence: 8th International Conference, ANTS 2012, volume 7461 of Lecture Notes in Computer Science, pages 168–179, Berlin, Germany, 2012. Springer. doi: 10.1007/978-3-642-32650-9_15. |
dc.relation.references | Eliseo Ferrante, Ali Emre Turgut, Edgar A. Duéñez-Guzmán, Marco Dorigo, y Tom Wenseleers. Evolution of self-organized task specialization in robot swarms. PLOS Computational Biology, 11(8):e1004273, 2015. doi: 10.1371/journal.pcbi.1004273. |
dc.relation.references | Simon Jones, Alan Winfield, Sabine Hauert, y Matthew Studley. Onboard evolution of understandable swarm behaviors. Advanced Intelligent Systems, 1(6):1900031, 2019. doi: 10.1002/aisy.201900031. |
dc.relation.references | Juan Jesús Roldán, Elena Peña-Tapia, David Garzón Ramos, Jorge de León, Mario Garzón, Jaime del Cerro, y Antonio Barrientos. Multi-robot systems, virtual reality and ROS: developing a new generation of operator interfaces. In Anis Koubaa, editor, Robot Operating System (ROS): The Complete Reference, volume 778 of SCI, pages 29–64. Springer, Cham, Switzerland, 2018. doi: 10.1007/978-3-319-91590-6_2. |
dc.relation.references | Mario Garzón, João Valente, Juan Jesús Roldán, David Garzón Ramos, Jorge de León, Antonio Barrientos, y Jaime del Cerro. Using ROS in multi-robot systems: experiences and lessons learned from real-world field tests. In Anis Koubaa, editor, Robot Operating System (ROS): The Complete Reference, volume 707 of SCI, pages 449–483. Springer, Cham, Switzerland, 2017. doi: 10.1007/978-3-319-54927-9_14. |
dc.relation.references | Anders Lyhne Christensen, Rehan O’Grady, y Marco Dorigo. From fireflies to fault-tolerant swarms of robots. IEEE Transactions on Evolutionary Computation, 13(4): 754–766, 2009. doi: 10.1109/TEVC.2009.2017516. |
dc.relation.references | Florian Berlinger, Melvin Gauci, y Radhika Nagpal. Implicit coordination for 3D underwater collective behaviors in a fish-inspired robot swarm. Science Robotics, 6(50):eabd8668, 2021. doi: 10.1126/scirobotics.abd8668. |
dc.relation.references | Juan Jesús Roldán, Jaime del Cerro, David Garzón Ramos, Pablo Garcia-Aunon, Mario Garzón, Jorge de León, y Antonio Barrientos. Robots in agriculture: state of art and practical experiences. In Antonio J. R. Neves, editor, Service Robots. IntechOpen, London, United Kingdom, 2017. doi: 10.5772/intechopen.69874. |
dc.relation.references | Simon Jones, Emma Milner, Mahesh Sooriyabandara, y Sabine Hauert. Distributed situational awareness in robot swarms. Advanced Intelligent Systems, 2(11):2000110, 2020. doi: 10.1002/aisy.202000110. |
dc.relation.references | Suet Lee y Sabine Hauert. Simulations, real robots, and bloopers from the DOTS competition: powering emergency food distribution using swarms. ROBOTS Association, Préverenges, Switzerland, 2021. Robohub. |
dc.relation.references | Heiko Hamann, Melanie Schranz, Wilfried Elmenreich, Vito Trianni, Carlo Pinciroli, Nicolas Bredeche, y Eliseo Ferrante. Editorial: designing self-organization in the physical realm. Frontiers in Robotics and AI, 7:164, 2020. doi: 10.3389/frobt.2020.597859. |
dc.relation.references | David St-Onge, Vivek Shankar Varadharajan, Švogor Ivan, y Giovanni Beltrame. From design to deployment: decentralized coordination of heterogeneous robotic teams. Frontiers in Robotics and AI, 7:51, 2020. doi: 10.3389/frobt.2020.00051. |
dc.relation.references | Gabriele Valentini, Eliseo Ferrante, y Marco Dorigo. The best-of-n problem in robot swarms: formalization, state of the art, and novel perspectives. Frontiers in Robotics and AI, 4:9, 2017. doi: 10.3389/frobt.2017.00009. |
dc.relation.references | Carlo Pinciroli y Giovanni Beltrame. Buzz: a programming language for robot swarms. IEEE Software, 33(4):97–100, 2016. doi: 10.1109/MS.2016.95. |
dc.relation.references | Rehan O’Grady, Anders Lyhne Christensen, y Marco Dorigo. SWARMORPH: multirobot morphogenesis using directional self-assembly. IEEE Transactions on Robotics, 25 (3):738–743, 2009. doi: 10.1109/TRO.2008.2012341. |
dc.relation.references | Rehan O’Grady, Roderich Groß, Anders Lyhne Christensen, y Marco Dorigo. Self-assembly strategies in a group of autonomous mobile robots. Autonomous Robots, 28 (4):439–455, 2010. doi: 10.1007/s10514-010-9177-0. |
dc.relation.references | Nithin Mathews, Anders Lyhne Christensen, Alessandro Stranieri, Alexander Scheidler, y Marco Dorigo. Supervised morphogenesis: exploiting morphological flexibility of self-assembling multirobot systems through cooperation with aerial robots. Robotics and Autonomous Systems, 112:154–167, 2019. doi: 10.1016/j.robot.2018.11.007. |
dc.relation.references | Eliseo Ferrante, Ali Emre Turgut, Nithin Mathews, Mauro Birattari, y Marco Dorigo. Flocking in stationary and non-stationary environments: a novel communication strategy for heading alignment. In Robert Schaefer, Carlos Cotta, Joanna Ko lodziej, y Günter Rudolph, editors, Parallel Problem Solving from Nature – PPSN XI: 11th International Conference, volume 6239 of Lecture Notes in Computer Science, pages 331–340, Berlin, Germany, 2010. Springer. doi: 10.1007/978-3-642-15871-1_34 |
dc.relation.references | Giovanni Pini, Arne Brutschy, Marco Frison, Andrea Roli, Marco Dorigo, y Mauro Birattari. Task partitioning in swarms of robots: an adaptive method for strategy selection. Swarm Intelligence, 5(3–4):283–304, 2011. doi: 10.1007/s11721-011-0060-1. |
dc.relation.references | Arne Brutschy, Lorenzo Garattoni, Manuele Brambilla, Gianpiero Francesca, Giovanni Pini, Marco Dorigo, y Mauro Birattari. The TAM: abstracting complex tasks in swarm robotics research. Swarm Intelligence, 9(1):1–22, 2015. doi: 10.1007/s11721-014-0102-6. |
dc.relation.references | Giovanni Pini, Arne Brutschy, Alexander Scheidler, Marco Dorigo, y Mauro Birattari. Task partitioning in a robot swarm: object retrieval as a sequence of subtasks with direct object transfer. Artificial Life, 20(3):291–317, 2014. doi: 10.1162/ARTL_a_00132. |
dc.relation.references | Anders Lyhne Christensen y Marco Dorigo. Evolving an integrated phototaxis and hole-avoidance behavior for a swarm-bot. In Luis M. Rocha, Larry S. Yaeger, Mark A. Bedau, Dario Floreano, Robert L. Goldstone, y Alessandro Vespignani, editors, Artificial Life X: Proceedings of the Tenth International Conference on the Simulation and Synthesis of Living Systems, pages 248–254, Cambridge, MA, USA, 2006. MIT Press. A Bradford Book. |
dc.relation.references | Nick Jakobi, Phil Husbands, y Inman Harvey. Noise and the reality gap: the use of simulation in evolutionary robotics. In F. Morán, A. Moreno, Juan J. Merelo, y P. Chacón, editors, Advances in Artificial Life: Third European Conference on Artificial Life, volume 929 of Lecture Notes in Artificial Intelligence, pages 704–720, Berlin, Germany, 1995. Springer. doi: 10.1007/3-540-59496-5_337. |
dc.relation.references | Antoine Ligot y Mauro Birattari. Simulation-only experiments to mimic the effects of the reality gap in the automatic design of robot swarms. Swarm Intelligence, 14:1–24, 2020. doi: 10.1007/s11721-019-00175-w. |
dc.relation.references | Stefano Nolfi y Dario Floreano. Evolutionary Robotics: The Biology, Intelligence, and Technology of Self-Organizing Machines. MIT Press, Cambridge, MA, USA, first edition, 2000. A Bradford Book. |
dc.relation.references | Jonas Kuckling, Vincent Van Pelt, y Mauro Birattari. AutoMoDe-Cedrata: automatic design of behavior trees for controlling a swarm of robots with communication capabilities. SN Computer Science, 2021. Submitted. |
dc.relation.references | Miquel Kegeleirs, David Garzón Ramos, y Mauro Birattari. Random walk exploration for swarm mapping. In Kaspar Althoefer, Jelizaveta Konstantinova, y Ketao Zhang, editors, Towards Autonomous Robotic Systems: 20th Annual Conference, TAROS 2019, volume 11650 of Lecture Notes in Computer Science, pages 211–222, Cham, Switzerland, 2019. Springer. doi: 10.1007/978-3-030-25332-5_19. |
dc.relation.references | Ryan A. Licitra, Zachary I Bell, y Warren E. Dixon. Single-agent indirect herding of multiple targets with uncertain dynamics. IEEE Transactions on Robotics, 35(4): 847–860, 2019. doi: 10.1109/TRO.2019.2911799. |
dc.relation.references | Katie Genter y Peter Stone. Influencing a flock via ad hoc teamwork. In Marco Dorigo, Mauro Birattari, Simon Garnier, Heiko Hamann, Marco Montes de Oca, Christine Solnon, y Thomas Stützle, editors, Swarm Intelligence: 9th International Conference, ANTS 2014, volume 8667 of Lecture Notes in Computer Science, pages 110–121, Cham, Switzerland, 2014. Springer International Publishing. doi: 10.1007/978-3-319-09952-1_10. |
dc.relation.references | Katie Genter y Peter Stone. Adding influencing agents to a flock. In AAMAS ’16: Proceedings of the 2016 International Conference on Autonomous Agents and Multi-agent Systems, pages 615–623, Richland, SC, USA, 2016. International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS). |
dc.relation.references | Anil Özdemir, Melvin Gauci, y Roderich Groß. Shepherding with robots that do not compute. In ECAL 2017, the Fourteenth European Conference on Artificial Life, Cambridge, MA, USA, 2017. MIT Press. doi: 10.7551/ecal_a_056. |
dc.relation.references | Alyssa Pierson y Mac Schwager. Controlling noncooperative herds with robotic herders. IEEE Transactions on Robotics, 34(2):517–525, 2018. doi: 10.1109/TRO.2017.2776308. |
dc.relation.references | Junyan Hu, Ali Emre Turgut, Tomáš Krajnı́k, Barry Lennox, y Farshad Arvin. Occlusion-based coordination protocol design for autonomous robotic shepherding tasks. IEEE Transactions on Cognitive and Developmental Systems, page 1, 2020. doi: 10.1109/TCDS.2020.3018549. |
dc.relation.references | Lorenzo Garattoni, Gianpiero Francesca, Arne Brutschy, Carlo Pinciroli, y Mauro Birattari. Software infrastructure for e-puck (and TAM). Technical Report TR/IRIDIA/2015-004, IRIDIA, Université Libre de Bruxelles, Brussels, Belgium, 2015. |
dc.relation.references | Muhammad Salman, David Garzón Ramos, Ken Hasselmann, y Mauro Birattari. Phormica: photochromic pheromone release and detection system for stigmergic coordination in robot swarms. Frontiers in Robotics and AI, 7:195, 2020. doi: 10.3389/frobt.2020.591402. |
dc.relation.references | Álvaro Gutiérrez, Alexandre Campo, Marco Dorigo, Jesus Donate, Félix Monasterio-Huelin, y Luis Magdalena. Open e-puck range & bearing miniaturized board for local communication in swarm robotics. In Kinugawa Kosuge, editor, 2009 IEEE International Conference on Robotics and Automation (ICRA), pages 3111–3116, Piscataway, NJ, USA, 2009. IEEE. doi: 10.1109/ROBOT.2009.5152456. |
dc.relation.references | École polytechnique fédérale de Lausanne. Omnidirectional vision turret for the e-puck. http://www.e-puck.org/index.php?option=com_content&view=article&id=26&Itemid=21, 2010. |
dc.relation.references | Ken Hasselmann, Antoine Ligot, Gianpiero Francesca, David Garzón Ramos, Muhammad Salman, Jonas Kuckling, Fernando J. Mendiburu, y Mauro Birattari. Reference models for AutoMoDe. Technical Report TR/IRIDIA/2018-002, IRIDIA, Université Libre de Bruxelles, Brussels, Belgium, 2018. |
dc.relation.references | Andreas Kolling, Phillip Walker, Nilanjan Chakraborty, Katia Sycara, y Michael Lewis. Human interaction with robot swarms: a survey. IEEE Transactions on Human-Machine Systems, 46(1):9–26, 2016. doi: 10.1109/THMS.2015.2480801. |
dc.relation.references | Nathan P. Koenig y Andrew Howard. Design and use paradigms for Gazebo, an open-source multi-robot simulator. In 2004 IEEE/RSJ International Conference On Intelligent Robots And Systems (IROS), volume 3, pages 2149–2154, Piscataway, NJ, USA, 2004. IEEE. doi: 10.1109/IROS.2004.1389727. |
dc.relation.references | Eric Rohmer, Surya P. N. Singh, y Marc Freese. V-REP: a versatile and scalable robot simulation framework. In 2013 IEEE/RSJ International Conference On Intelligent Robots And Systems (IROS), volume 3, pages 1321–1326, Piscataway, NJ, USA, 2013. IEEE. doi: 10.1109/IROS.2013.6696520. |
dc.relation.references | Lenka Pitonakova, Manuel Giuliani, Anthony Pipe, y Alan Winfield. Feature and performance comparison of the V-REP, Gazebo and ARGoS robot simulators. In Manuel Giuliani, Tareq Assaf, y Maria Elena Giannaccini, editors, Towards Autonomous Robotic Systems: 19th Annual Conference, TAROS 2018, Lecture Notes in Computer Science, pages 357–368, Cham, Switzerland, 2018. Springer. doi: 10.1007/978-3-319-96728-8_30. |
dc.relation.references | Vito Trianni y Manuel López-Ibáñez. Advantages of task-specific multi-objective optimisation in evolutionary robotics. PLOS ONE, 10(8):e0136406, 2015. doi: 10.1371/journal.pone.0136406. |
dc.relation.references | Antoine Ligot, Ken Hasselmann, y Mauro Birattari. AutoMoDe-Arlequin: neural networks as behavioral modules for the automatic design of probabilistic finite state machines. In Marco Dorigo, Thomas Stützle, Marı́a J. Blesa, Christian Blum, Heiko Hamann, Mary Katherine Heinrich, y Volker Strobel, editors, Swarm Intelligence: 12th International Conference, ANTS 2020, volume 12421 of Lecture Notes in Computer Science, pages 109–122, Cham, Switzerland, 2020. Springer. doi: 10.1007/978-3-030-60376-2_21. |
dc.relation.references | Gaëtan Spaey, Miquel Kegeleirs, David Garzón Ramos, y Mauro Birattari. Evaluation of alternative exploration schemes in the automatic modular design of robot swarms. In Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, y Gilles Louppe, editors, Artificial Intelligence and Machine Learning: BNAIC 2019, BENELEARN 2019, volume 1196 of Communications in Computer and Information Science, pages 18–33. Springer, Cham, Switzerland, 2020. doi: 10.1007/978-3-030-65154-1_2. |
dc.relation.references | Johann Borenstein y Yorem Koren. Real-time obstacle avoidance for fast mobile robots. IEEE Transactions on Systems, Man, and Cybernetics, 19(5):1179–1187, 1989. doi: 10.1109/21.44033. |
dc.relation.references | Ken Hasselmann, Frédéric Robert, y Mauro Birattari. Automatic design of communication-based behaviors for robot swarms. In Marco Dorigo, Mauro Birattari, Simon Garnier, Heiko Hamann, Marco Montes de Oca, Christine Solnon, y Thomas Stützle, editors, Swarm Intelligence: 11th International Conference, ANTS 2018, volume 11172 of Lecture Notes in Computer Science, pages 16–29, Cham, Switzerland, 2018. Springer. doi: 10.1007/978-3-030-00533-7_2. |
dc.relation.references | Manuel López-Ibáñez, Jérémie Dubois-Lacoste, Leslie Pérez Cáceres, Mauro Birattari, y Thomas Stützle. The irace package: iterated racing for automatic algorithm configuration. Operations Research Perspectives, 3:43–58, 2016. doi: 10.1016/j.orp.2016.09.002. |
dc.relation.references | Mauro Birattari, Thomas Stützle, Luis Paquete, y Klaus Varrentrapp. A racing algorithm for configuring metaheuristics. In William B. Langdon, Erick Cantú-Paz, Keith Mathias, Rajkumar Roy, David Davis, Riccardo Poli, Karthik Balakrishnan, Vasant Honavar, Günter Rudolph, Joachim Wegener, Lary Bull, Mitchell A. Potter, Alan C. Schultz, Julian F. Miller, Edmund K. Burke, y Natasha Jonoska, editors, GECCO’02: Proceedings of the 4th Annual Conference on Genetic and Evolutionary Computation, pages 11–18, San Francisco, CA, USA, 2002. Morgan Kaufmann Publishers. |
dc.relation.references | Nikolaus Hansen y Andreas Ostermeier. Completely derandomized self-adaptation in evolution strategies. Evolutionary Computation, 9(2):159–195, 2001. doi: 10.1162/106365601750190398. |
dc.relation.references | Tobias Glasmachers, Tom Schaul, Sun Yi, Daan Wierstra, y Jürgen Schmidhuber. Exponential natural evolution strategies. In GECCO’10: Proceedings of the 12th annual conference on Genetic and evolutionary computation, pages 393–400, New York, NY, USA, 2010. ACM. doi: 10.1145/1830483.1830557. |
dc.relation.references | Kenneth O. Stanley y Risto Miikkulainen. Evolving neural networks through augmenting topologies. Evolutionary Computation, 10(2):99–127, 2002. doi: 10.1162/106365602320169811. |
dc.relation.references | Jonas Kuckling, Ken Hasselmann, Vincent Van Pelt, Cédric Kiere, y Mauro Birattari. AutoMoDe Editor: a visualization tool for AutoMoDe. Technical Report TR/IRIDIA/2021-009, IRIDIA, Université Libre de Bruxelles, Brussels, Belgium, 2021. |
dc.relation.references | W. J. Conover. Practical Nonparametric Statistics. Wiley Series in Probability and Statistics. John Wiley & Sons, New York, NY, USA, third edition, 1999. |
dc.relation.references | Mauro Birattari. Notes on the estimation of the expected performance of automatic methods for the design of control software for robot swarms. Technical Report TR/IRIDIA/2020-10, IRIDIA, Université Libre de Bruxelles, Brussels, Belgium, 2020. |
dc.relation.references | Haoxiang Zhang y Lei Liu. Intelligent control of swarm robotics employing biomimetic deep learning. 9(10):236, 2021. doi: 10.3390/machines9100236. |
dc.rights.accessrights | info:eu-repo/semantics/openAccess |
dc.subject.proposal | Robótica de enjambres |
dc.subject.proposal | Diseño automático |
dc.subject.proposal | Diseño manual |
dc.subject.proposal | AutoMoDe |
dc.subject.proposal | Neuroevolución |
dc.subject.proposal | Coordinación entre enjambres |
dc.subject.proposal | Swarm robotics |
dc.subject.proposal | Automatic design |
dc.subject.proposal | Manual design |
dc.subject.proposal | AutoMoDe |
dc.subject.proposal | Neuroevolution |
dc.subject.proposal | Coordination between robot swarms |
dc.title.translated | Empirical comparison of methods for the design of robot swarms: a simulation study of swarms that coordinate other swarms. |
dc.type.coar | http://purl.org/coar/resource_type/c_bdcc |
dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa |
dc.type.content | Image |
dc.type.content | Text |
oaire.accessrights | http://purl.org/coar/access_right/c_abf2 |
oaire.fundername | El desarrollo de esta tesis ha contado con financiación del proyecto DEMIURGE (ERC grant agreement No 681872, PI Mauro Birattari) y con la financiación del Ministerio Colombiano de Ciencia, Tecnología e Innovación–Minciencias. |
dcterms.audience.professionaldevelopment | Bibliotecarios |
dcterms.audience.professionaldevelopment | Estudiantes |
dcterms.audience.professionaldevelopment | Investigadores |
dc.description.curriculararea | Eléctrica, Electrónica, Automatización Y Telecomunicaciones |
Files in this item
This item appears in the following Collection(s)
This work is licensed under a Creative Commons Reconocimiento-NoComercial 4.0.This document has been deposited by the author (s) under the following certificate of deposit