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  • 标题:Finding Objects with Segmentation Strategy based Multi Robot Exploration in Unknown Environment
  • 本地全文:下载
  • 作者:Reza Arezoumand ; Reza Arezoumand ; Syamsiah Mashohor
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2013
  • 卷号:97
  • 页码:580-586
  • DOI:10.1016/j.sbspro.2013.10.276
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractIn this paper we address exploration algorithm in flat experimental environment with colored objects for multi robots system. The aim of exploration in unknown environment is finding target points like mine detection in outdoor environment without any positioning device. Two algorithms were investigated in this paper one is frontier based random search algorithm and the second is efficient algorithm based on segmentation strategy. To improve efficiency, each robot had to go to different regions to avoid cumulating robots in one region. Constructed maps for all four regions could be shared and navigation could be done more effectively. For constructing map robot can use on built range finder sensor or using vision based systems. Also the algorithm using segmentation strategy is using frontier base algorithm for exploring divided area. Both algorithm implemented and analyzed in Player/Stage simulation. The result was compared and showed the efficiency of the designed algorithm based segmentation strategy. In simulation this algorithm is tested with different number of robots to achieve better view of efficiency for proposed algorithm in different type of environment like harsh environment as possibility of losing some robots.
  • 关键词:Multi-robot exploration;Flocking;Exploration ratio;Trajectory prediction
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