[1]屈云豪,丁永生,郝矿荣,等.行军启发的多机器人紧密队形保持策略[J].智能系统学报,2018,13(5):673-679.[doi:10.11992/tis.201710023]
QU Yunhao,DING Yongsheng,HAO Kuangrong,et al.March-inspired multi-robot compact formation strategy[J].CAAI Transactions on Intelligent Systems,2018,13(5):673-679.[doi:10.11992/tis.201710023]
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QU Yunhao,DING Yongsheng,HAO Kuangrong,et al.March-inspired multi-robot compact formation strategy[J].CAAI Transactions on Intelligent Systems,2018,13(5):673-679.[doi:10.11992/tis.201710023]
行军启发的多机器人紧密队形保持策略
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
13
期数:
2018年第5期
页码:
673-679
栏目:
学术论文—智能系统
出版日期:
2018-09-05
- Title:
- March-inspired multi-robot compact formation strategy
- 分类号:
- TP242
- 摘要:
- 多机器人协同编队是多机器人研究的关键技术之一，是通过控制队伍中的机器人，使其按照预定的队形进行前进。本文基于领航者-追随者结构的编队控制方法，从军队急行军中得到启发，设计了同列依次替补和末排向内收拢原则，提出多机器人紧密队形保持策略。并引入能耗和队形紧密度两个编队性能评价指标，验证了多机器人紧密队形保持策略的优越性。仿真实验证明了多机器人紧密队形保持策略的有效性。
- Abstract:
- Multi-robot collaborative formation is one of the key technologies of multi-robot research. By controlling the robots in the team, the multi-robot cooperative formation can move forward according to the predetermined formation. Based on the formation control method of the leader-follower structure, and inspired by the rapid march of the army, this paper presents two principles:sequential substitution in the same column and inward convergence in the last row, and a multi-robot compact formation strategy is proposed. Two formation performance evaluation indicators of energy consumption and formation compactness are introduced, which verifies the superiority of the multi-robot compact formation strategy. Finally, the simulation result proves the efficiency of the multi-robot compact formation strategy.
- 参考文献/References:
-
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QIAN Dianwei.Formation control of multi-robot systems in a fuzzy sliding mode[J].CAAI Transactions on Intelligent Systems,2016,11():641.[doi:10.11992/tis.201510017]
备注/Memo
收稿日期:2017-10-28。
基金项目:国家自然科学基金项目（61473077，61473078，61503075，61603090）；上海市科学技术委员会国际合作项目（16510711100）；中央高校基本科研业务费专项资金资助项目（2232017D-08，2232017D-13）；上海市扬帆计划项目（17YF1426100）.
作者简介:屈云豪,男,1992年生,硕士研究生,主要研究方向为智能系统、网络智能、智能机器人;丁永生,男,1967年生,教授,博士生导师,博士,主要研究方向为智能系统、网络智能、智能物联网、智能机器人。主持国家自然科学基金重点项目30余项,授权国家发明专利43项。发表学术论文200余篇,被SCI收录100余篇,出版专著7部,参编6部国际编著;郝矿荣,女,1964年生,教授,博士生导师,主要研究方向为类脑智能、机器视觉、智能系统、智能机器人、智能物联网。获得国家发明专利授权27项。发表学术论文150余篇,被SCI收录70余篇,出版专著3部。
通讯作者:郝矿荣.E-mail:krhao@dhu.edu.cn.
更新日期/Last Update:
2018-10-25