Currently, the researchers have made a lot of hybrid particle swarm algorithm in order to solve the shortcomings that the Particle Swarm Algorithms is easy to converge to local extremum, these algorithms declare that there has been better than the standard particle swarm. This study selects three kinds of representative hybrid particle swarm optimizations (differential evolution particle swarm ...

Human interaction with robot swarms (HSI) is a young field with very few user studies that explore operator behavior. All these studies assume perfect communication between the operator and the swarm. A key challenge in the use of swarm robotic systems in human supervised tasks is to understand human swarm interaction in the presence of limited communication bandwidth, which is a constraint ari...

This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these freero...

With the rapid development of swarm intelligence research field, a large number of algorithms in swarm intelligence are proposed one after another. The strong points and the drawbacks of a specific swarm intelligence algorithm becomes clear to be seen when the number of its application increases. To overcome the handicaps, some hybrid methods are invented. In this review, three hybrid swarm int...

numerous problems encountered in real life cannot be actually formulated as a single objective problem; hence the requirement of multi-objective optimization (moo) had arisen several years ago. due to the complexities in such type of problems powerful heuristic techniques were needed, which has been strongly satisfied by swarm intelligence (si) techniques. particle swarm optimization (pso) has ...

In this paper, an optimal stable algorithm is presented for members of a robots swarm moving toward a target. Equations of motion of the swarm are based on Lagrangian energy equations. Regarding of similar research On the design of swarm motion algorithm, an equation of motion considered constraints to guarantee no collision between the members and the members and obstacles along the motion pat...

Of realistic swarm biology engineering: model simplification and tuning for IT applications.Combines an overview of swarm intelligence with an up-to-date treatment of the. With the biological foundations, optimization, swarm robotics, and applications in. swarm intelligence introduction and applications pdf wide-range applications of swarm intelligence algorithms is presented in many.applicatio...

Human interaction with robot swarms (HSI) is a young field with very few user studies that explore operator behavior. All these studies assume perfect communication between the operator and the swarm. A key challenge in the use of swarm robotic systems in human supervised tasks is to understand human swarm interaction in the presence of limited communication bandwidth, which is a constraint ari...

Swarm intelligence can provide robust, adaptable, scalable solutions to difficult problems. The distributed nature of swarm activity is the basis of these desirable qualities, but it also prevents swarm-based techniques from having direct access to global knowledge that could facilitate the task at hand. Our experiments indicate that a swarm system can use an auxiliary swarm, called a communica...

This paper presents a new approach to control robots, which can quickly find their swarm while tracking a moving target through the obstacles of the environment. In this approach, an artificial potential field is generated between each free-robot and the virtual attractive point of the swarm. This artificial potential field will lead free-robots to their swarm. The swarm-finding of these freero...