A survey of swarm robotics system

Authors:
Zhiguo Shi;Jun Tu;Qiao Zhang;Lei Liu;Junming Wei
Affiliations:
School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, P.R.China;School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, P.R.China;School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, P.R.China;School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, P.R.China;ANU College of Engineering and Computer Science, Australian National University, Canberra, Australia
Venue:
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
Year:
2012

Citing 7
Cited 0

Swarm intelligence

Swarm intelligence
Learning and Measuring Specialization in Collaborative Swarm Systems

Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Self-organizing sync in a robotic swarm: a dynamical system view

IEEE Transactions on Evolutionary Computation
Optimized stochastic policies for task allocationin swarms of robots

IEEE Transactions on Robotics
Swarm robotics: from sources of inspiration to domains of application

SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
The SWARM-BOTS project

SAB'04 Proceedings of the 2004 international conference on Swarm Robotics
Autonomous Self-Assembly in Swarm-Bots

IEEE Transactions on Robotics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Swarm robotics system has been a particularly active topic of robotics in recent years due to the increasing deepening of research on robotics technology and application. This paper gives a survey of swarm robotics system research from such aspects as theoretical basis and physical research, simulation platform, distributed control information fusion and communications system. Some problems that need to be solved about swarm robotics system research in IOT (Internet of Things) environment are also raised, such as co-adaptation, distributed control and self-organization, resource scheduling management. Finally, the ant colony algorithm and particle swarm optimization are applied to the swarm robotics system.