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During collective construction tasks, swarm robots coordinate their actions in space and time to build structures that conform to some given design or specification. In this paper, a simulation model and a mathematical model (based on a Markov chain) are introduced to describe the deposition process of a previously detailed robotic swarm system that uses templates and feedback to facilitate con...

Based on the life cycle cost (LCC) approach, this paper presents an integral mathematical model and particle swarm optimization (PSO) algorithm for the heating system planning (HSP) problem. The proposed mathematical model minimizes the cost of heating system as the objective for a given life cycle time. For the particularity of HSP problem, the general particle swarm optimization algorithm was...

Original scientific paper This paper offers an improved technique namely, Quorum sensing based Bacterial Swarm Optimization (QBSO) technique to solve Practical Dynamic Economic Dispatch (PDED) problem. Quorum sensing is the communication signalling mechanism that permits the bacteria to organize the collective behaviour. The enhanced QBSO method improves the exploration capability of bacterial ...

The paper focuses on a capacitated vehicle routing problem with two objectives: one is attainment of specific load factor and the other is minimization of total travel cost. Our approach is based on artificial fish swarm algorithm, a swarm-based heuristic, which mimics the foraging behaviour of a fish swarm. After initializing a school of artificial fish, whose validity is guaranteed by a desig...

Rapid advancements of both microsystem technology and multi-agent systems have generated a new discipline, arising from the fusion of microrobotics technologies and of swarm intelligence theories. Microrobotics contributes with new capabilities in manipulating objects in the microscale and in developing miniaturized intelligent machines, while swarm intelligence supplies new algorithms allowing...

In practical applications of robot swarms with bioinspired behaviors, a human operator will need to exert control over the swarm to fulfill the mission objectives. In many operational settings, human operators are remotely located and the communication environment is harsh. Hence, there exists some latency in information (or control command) transfer between the human and the swarm. In this pap...

This chapter considers the application of swarm intelligence principles to collective robotics. Our aim is to identify the reasons for the growing interest in the intersection of these two areas, and to evaluate the progress that has been made to date. In the course of this chapter, we will discuss the implications of taking a swarm intelligent approach, and review recent research and applicati...

The approaches in this work combine the swarm behavior principles of Craig W. Reynolds with space filling curves movements. We intend to evaluate how the entire swarm moves by including a deterministic leader behavior for some agents. Therefore, we examine different combinations of Hilbert Curves with the classical swarm algorithms. We introduce a practical problem, the collection of manganese ...

We present an algorithm that is inspired by theoretical and empirical results in social learning and swarm intelligence research. The algorithm is based on a framework that we call incremental social learning. In practical terms, the algorithm is a hybrid between a local search procedure and a particle swarm optimization algorithm with growing population size. The local search procedure provide...