Flexible multi-robot formation control: Partial formations as physical data structures

Michael De Denus*, John Anderson, Jacky Baltes

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

摘要

Formations are often seen in nature, and bring many benefits for the group as a whole. They can allow a group to explore a large area more effectively, can ease movement of the group through the environment, and can increase group perceptual coverage and increase defensive capabilities, for example. The benefits of any particular formation vary and are obtained from the structure the formation provides. Robotic formations can have similar applications. To date, the techniques used and formations employed in robotic applications are significantly simpler than those seen in nature. Current techniques often require some level of global knowledge, central processing or other unrealistic assumptions. We seek to develop a formation control technique that has as few of these limitations as possible. Each agent under our approach has only local knowledge of the environment, uses no broadcast communication, and can communicate only over a limited range. Formations are achieved by organizing agents into a graph structure, where agents occupying the vertices take on the role of maintaining an appropriate number of agents on each edge, thus preserving the formation's shape and scale. We do not assume a known or static population: the evolving formation acts as a physical data structure to assist in placing and rearranging agents as the population changes. This approach does not require a global coordinate system, fixed positions within the formation, or any single lead agent. All agents within our approach are peers, and any can adopt any role within the formation.

原文英語
主出版物標題Multirobot Systems and Physical Data Structures - Papers from the AAAI Spring Symposium, Technical Report
發行者AI Access Foundation
頁面4-9
頁數6
ISBN(列印)9781577354994
出版狀態已發佈 - 2011
事件2011 AAAI Spring Symposium - Stanford, CA, 美国
持續時間: 2011 三月 212011 三月 23

出版系列

名字AAAI Spring Symposium - Technical Report
SS-11-07

其他

其他2011 AAAI Spring Symposium
國家/地區美国
城市Stanford, CA
期間2011/03/212011/03/23

ASJC Scopus subject areas

  • 人工智慧

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