Swarm Intelligence (SI) refers to the complex collective behavior of self-organized and decentralized systems, typically composed of a (spatially distributed and often large) population of individuals, or agents. These agents interact among them and with the environment in different but simple and local ways, coordinating their actions, and making the swarm inherently robust, effective, and flexible. A plethora of application scenarios have hitherto resorted to SI when addressing optimization, inference and prediction tasks. Among them, Swarm robotics (SR) refers to the application of SI methods to scenarios where the population of agents is embodied by physical or simulated robotic devices. The focus of SR is to thoroughly analyze how a swarm comprised of relatively simple physically embodied robots can be controlled to collectively accomplish different kind of goals that are out of the common capabilities of a single robot. Algorithms and methods relying on SR have been so far exceled over a wide range of complex real-world problems, such as localization, mining, disaster rescue missions, agricultural foraging or scenery mapping problems. The interests in SR form a popular topic that lays at the core of many research activities and contributions in the literature. This special issue aims at disseminating the latest findings and research achievements in the areas of SI and SR, with an intention to balance between theoretical research ideas and their practicability as well as industrial applicability. To this end, scholars and practitioners from academia and industrial fields are invited to submit high-quality original contributions to this special issue.
Topics of interest include, but are not limited to:
Recent advances on Soft Computing methods for Robotics, with an emphasis on those inspired by processes and behaviors typically observed in Nature
Novel applications of Swarm Robotics, with a priority on real-world scenarios.
Hybridization of Swarm Intelligence techniques, with applications to robotics or autonomous complex systems.
New synergies between Swarm Intelligence and Swarm Robotics.
Coordination and control of Swarm Robotic Systems.
Adaptive Soft Computing methods.
Applications of Swarm Intelligence for collaborative positioning and route optimization in robotic swarms.
Distributed inference in Swarm Robotics.
Self-organization in robotics enabled by Swarm Intelligence.
Distributed Swarm Robotic systems.
June 1, 2018: Call for papers.
August 1, 2018: Deadline for Initial Paper Submission.
November 1, 2018: Notification of First Round Decision.
December 15, 2018: Deadline for Revised Paper Submission.
February 15, 2019: Final acceptance decision.
June 1, 2019: Target publication date.
Dr. Eneko Osaba Icedo ([email protected])
TECNALIA Research and Innovation
Prof. Dr. Javier Del Ser ([email protected])
University of the Basque Country (UPV/EHU) and Basque Center for Applied Mathematics (BCAM)
Prof. Dr. Andrés Iglesias ([email protected])
Toho University and University of Cantabria
Prof. Dr. Xin-She Yang ([email protected])
SUBMISSION AND REVIEW OF PAPERS
Submitted papers should be original and are not be under consideration elsewhere for publication. The authors should follow the journal guidelines, regarding the manuscript content and its format when preparing their manuscripts. All papers will be reviewed by at least three independent reviewers for their suitability in terms of technical novelty, scientific rigor, scope, and relevance to this special issue.
Please select article type name of “VSI: Soft Computing&Robotics” during submission process.