We present a modified version of the Particle swarm Optimization algorithm in which we adjust the virtual swarm search by incorporating inter-agent dynamics native to multi-robot search scenarios. The neighborhood structure of PSO is modified to accurately represent feasible neighborhoods in multiple robot systems with limited communication in several different ways. The new algorithms are test...

The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently developed locally oriented paradigm. Benchmark testing of both paradigms is described, and applications, including neural network training and robot task learning, are proposed. Relationships between particle swarm optimization ...

A robot swarm is a collection of simple robots designed to work together to carry out some task. Such swarms rely on: the simplicity of the individual robots; the fault tolerance inherent in having a large population of identical robots; and the self-organised behaviour of the swarm as a whole. Although robot swarms present an attractive solution to demanding real-world applications, designing ...

Swarm robotics is concerned with the decentralised coordination of multiple robots having only limited communication and interaction abilities. Although fault tolerance and robustness to individual robot failures have often been used to justify the use of swarm robotic systems, recent studies have shown that swarm robotic systems are susceptible to certain types of failure. In this paper we pro...

This paper presents designing an optimal adaptive controller for tracking control of robot manipulators based on particle swarm optimization (PSO) algorithm. PSO algorithm has been employed to optimize parameters of the controller and hence to minimize the integral square of errors (ISE) as a performance criteria. In this paper, an improved PSO using logic is proposed to increase the convergenc...

Autonomous swarm algorithms and human-robot interaction (HRI) have both attracted increasing attention from researchers in recent years. However, HRI has rarely extended beyond single robots or small multi-robot teams. While one of the benefits of robot swarms is their robust capabilities and the ability of their distributed algorithms to deal autonomously with the complex interactions amongst ...

In recent days, self-assembling swarm robots have been studied by a number of researchers due to their advantages such as high efficiency, stability, and scalability. However, there are still critical issues in applying them to practical problems in the real world. The main objective of this study is to develop a novel self-assembling swarm robot algorithm that overcomes the limitations of exis...

Conventional particle swarm optimisation relies on exchanging information through social interaction among individuals. However for real-world problems involving control of physical agents (i.e., robot control), such detailed social interaction is not always possible. In this study, we propose the Perceptive Particle Swarm Optimisation algorithm, in which both social interaction and environment...

We describe a theory from Herbert Simon that links the structure of complex systems to increased speed of evolution, and argue the position that this theory can be beneficial to evolutionary swarm robotic research. We propose a way of applying this theory to evolutionary swarm robotic systems by manually designing the robot to robot communication mechanisms and keeping these constant, whilst ev...

In the motion control of a microrobot swarm, a key issue is how to autonomously generate a set of common coordinates among all robots and how to notify each robot of its heading direction in the generated common coordinates without any special devices for estimating location and bearing. This paper proposes a set of common coordinates and a heading direction generation method for a robot swarm ...