Inspired by social animals, such as ants, bees and fish, which appear to exhibit what has been dubbed ‘swarm intelligence’, swarm robotic systems aim to accomplish goals that are unachievable by an individual robot. Swarm robotics have a large number of potential uses, including applications in the military, monitoring, disaster relief, healthcare and commercial applications. To be able to achi...

A swarm is a decentralized and selforganized collective with lots of simple but autonomous and homogeneous individuals. Swarm intelligence is defined to describe its emergent behaviors. Both Sensor networks and mobile multi-robots can have swarm features. The combination and cooperation of these two systems is a tendency recently. From the view of swarm organisms, the challenges of combination ...

One of the benefits of using Combs disjunctive control in swarm intelligence is the ability of the swarm to continue to operate even when one or more of its sensors are broken. Instead of failing, the swarm continues to perform based on the inputs of the remaining sensors. In this project, a multi-objective scenario is designed for a swarm of agents to complete. Once optimized, the swarm is the...

We present a novel model of crowd motion and swarm behaviour, in the form of a multi-agent system. We introduce a set of behavioural rules arising from an individual’s presence within a swarm of other individuals. First, the separation force causes every agent to maintain a comfortable distance from all others in the same swarm. Second, the alignment force causes every agent in the same swarm t...

In this brief article we specify an “individual-based” continuous time model for swarm aggregation in n-dimensional space and study its stability properties. We show that the individuals (autonomous agents or biological creatures) will form a cohesive swarm in a finite time. Moreover, we obtain an explicit bound on the swarm size, which depends only on the parameters of the swarm model.

Case-based reasoning (CBR) is a useful technique to support decision making (DM) by learning from past experiences. It solves a new problem by retrieving, reusing, and adapting past solutions to old problems that are closely similar to the current problem. In this paper, we combine fuzzy logic with case-based reasoning to identify useful cases that can support the DM. At the beginning, a fuzzy ...

In this paper we present the first study of human-swarm interaction comparing two fundamental types of interaction, coined intermittent and environmental. These types are exemplified by two control methods, selection and beacon control, made available to a human operator to control a foraging swarm of robots. Selection and beacon control differ with respect to their temporal and spatial influen...

This review paper sets out to explore the question of how future complex engineered systems based upon the swarm intelligence paradigm could be assured for dependability. The paper introduces the new concept of ‘swarm engineering’: a fusion of dependable systems engineering and swarm intelligence. The paper reviews the disciplines and processes conventionally employed to assure the dependabilit...

The diversity and applicability of swarm intelligence is increasing everyday in the fields of science and engineering. Swarm intelligence gives the features of the dynamic features optimization concept. We have used swarm intelligence for the process of feature optimization and feature selection for content-based image retrieval. The performance of content-based image retrieval faced the proble...

In this paper, we study coordinated motion in a swarm robotic system, called a swarm-bot. A swarm-bot is a self-assembling and self-organizing artifact, composed of a swarm of s-bots, mobile robots with the ability to connect to and disconnect from each other. The swarm-bot concept is particularly suited for tasks that require abilities of navigation on rough terrain, such as space exploration ...