Open AccessStudy on efficient control of swarm robot using mobile agents and swarm intelligence
Author(s) -
Yahiko Kambayashi,
Munehiro Takimoto
Publication year - 2020
Publication title -
impact
Language(s) - English
Resource type - Journals
eISSN - 2398-7081
pISSN - 2398-7073
DOI - 10.21820/23987073.2020.4.65
Subject(s) - automation , flexibility (engineering) , robot , swarm behaviour , process (computing) , productivity , function (biology) , control (management) , computer science , swarm robotics , mobile robot , swarm intelligence , ant robotics , work (physics) , robotics , artificial intelligence , human–computer interaction , engineering , robot control , management , particle swarm optimization , operating system , mechanical engineering , evolutionary biology , biology , machine learning , economics , macroeconomics
Automation of tasks is a rapidly evolving process. The expansion of robots into industry has been ongoing for some time. Automation of factories and industrial processes has increased productivity and also meant humans no longer have to engage in dangerous, back-breaking labour. While the robots taking over this work have mostly been large, single purpose machines designed to carry out one or two functions, there is a growing demand for smaller, lighter and more flexible robots. These machines are being built to work as cooperative swarms or fleets. In this way they can be distributed in an environment and through communication networks maintain contact and coordinated function. This flexibility and small size again mean they can replace humans when tasks are either too dangerous or physically impossible for a person to complete. The hardware side of this technology is largely in place, however, the challenge now is how best to coordinate the movements of multiple robots remotely. Professor Yasushi Kambayashi and a team of researchers based at the Department of Computer and Information Engineering, Nippon Institute of Technology in Japan, is developing a new, decentralised control system that takes inspiration from social insects like ants.