��nsans��z Ara��larla D��zlemsel Olmayan Ara��lar��n Taranmas��

Autor: Seylan, ��a��lar, Bican, ��zg��r Sayg��n, Semiz, Fatih
Rok vydání: 2020
Předmět:
DOI: 10.48550/arxiv.2003.09310
Popis: The importance of area coverage with unmanned vehicles, in other words, traveling an area with an unmanned vehicle such as a robot or a UAV completely or partially with minimum cost, is increasing with the increase in usage of such vehicles today. Area coverage with unmanned vehicles is used today in the exploration of an area with UAVs, sweeping mines with robots, cleaning ground with robots in large shopping malls, mowing lawn in a large area etc. The problem has versions such as area coverage with a single unmanned vehicle, area coverage with multiple unmanned vehicles, on-line area coverage (The map of the area that will be covered is not known before starting the coverage) with unmanned vehicles etc. In addition, the area may have obstacles that the vehicles cannot move over. Naturally, many researches are working on the problem and a lot of researches have been done on the problem until today. Spanning tree coverage is one of the major approaches to the problem. In this approach, at the basic level, the planar area is divided into identical squares according to the range of sight of the vehicle, and centers of these squares are assumed to be vertexes of a graph. The vertexes of this graph are connected with the edges with unit costs and after finding the minimum spanning tree of the graph, the vehicle strolls around the spanning tree. The method we propose suggests a way to cover a non-planar area with unmanned vehicles. The method we propose also takes advantage of the spanning-tree coverage approach, but instead of assigning unit costs to the edges, we assigned a weight to each edge using slopes between vertexes those the edges connect. We have gotten noticeably better results than the results we got when we did not consider the slope between two squares and used the classical spanning tree approach.
in Turkish language
Databáze: OpenAIRE