Known as an artificial intelligence subarea, Swarm Robotics is a developing study field investigating bio-inspired collaborative control approaches and integrates a huge collection of agents, reasonably plain robots, in a distributed and decentralized manner. It offers an inspiring essential platform for new researchers to be engaged and share new knowledge to examine their concepts in analytical and heuristic strategies. This paper introduces an overview of current activities in Swarm Robotics and examines the present literature in this area to establish to approach between a realistic swarm robotic system and real-world enforcements. First, we review several Swarm Intelligence concepts to define Swarm Robotics systems, reporting their essential qualities and features and contrast them to generic multi-robotic systems. Second, we report a review of the principal projects that allow realistic study of Swarm Robotics. We demonstrate knowledge regarding current hardware platforms and multi-robot simulators. Finally, the forthcoming promissory applications and the troubles to surpass with a view to achieving them have been described and analyzed.
Convex Flow Balancing Network DesignIn this work, the single source tree network design problem under convex costs is addressed. This is a referential problem when designing networks for materials, energy or data transportation. The modeling effort yields a large scale mixedinteger nonlinear program which is very hard to solve. In order to overcome the solution difficulties, two distinct solution methods are deployed: The first of them is the Generalized Benders Decomposition method; the second technique combines the Outer Approximation method with the ideas of projection in Benders Decomposition in order to imply the technique Hybrid-OA. The Hybrid-OA method is very effective on solving instances up to 702 edges, under reasonable computational costs, and makes the further application of the proposed technique to even more sophisticated models promising.
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