Open AccessAnalytical and numerical modelling of the programmable percolation route formation when planning two-phase operations
Author(s) -
Y. A. Mostovoi,
V. A. Berdnikov
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1745/1/012066
Subject(s) - swarm behaviour , payload (computing) , robot , computer science , phase (matter) , percolation (cognitive psychology) , task (project management) , swarm robotics , service (business) , signal (programming language) , particle swarm optimization , real time computing , distributed computing , algorithm , artificial intelligence , engineering , computer network , chemistry , economy , organic chemistry , systems engineering , neuroscience , network packet , economics , biology , programming language
A swarm of robots, as a system of relatively simple interconnected managed objects, performs a common task simultaneously and in a distributed manner. When planning swarm operations associated with the creation in the service area through the front strip of the zones of the trust instrument - payload objects swarm, there is a problem of transmitting a signal from one robot to another for operational rearrangement of the swarm, as at the time of planning the exact purpose of the swarm operation has not yet been determined, or is a secret, or is determined by a number of random circumstances. The execution of the swarm operation is advisable to carry out in two phases, and the first phase to start even before the resolution of these uncertainties by creating a basic random network with a small concentration of robots in it. In the second phase of the operation, a programmable percolation route is formed by local rearrangement of the robots, which provides target coverage of the target equipment of the swarm objects of a certain service zone. In this case, you can significantly reduce the time of the operation. The corresponding analytical dependences were obtained.