Special Issue on Soft Computing for Swarm Robotics: New Trends and Applications
This Special Issue in the Journal of Computational Science aims at disseminating the latest findings and research achievements in the areas of Swarm Intelligence and Swarm Robotics, with an intention to balance between theoretical research ideas and their practicability as well as industrial applicability. 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.