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J4  2010, Vol. 44 Issue (4): 722-727    DOI: 10.3785/j.issn.1008-973X.2010.04.017
    
Optimal efficiency of multi-robot formation transform
JIANG Rongxin, ZHANG Liang, TIAN Xiang, CHEN Yaowu
Institute of Advanced Digital Technologies and Instrumentation, Zhejiang University, Hangzhou 310027, China
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Abstract  

An optimal efficiency model for multi-robot formation transform was proposed. The multirobot formation transform is divided into static transform mode and dynamic transform mode, and the formation energy consumption (FEC) and the formation convergence time (FCT) are adopted to evaluate the efficiency of formation transform. The optimal FEC model is a minimization model which minimizes the displaced distance sum of every robot. The optimal FCT model is a maxmin model which minimizes the maximal displaced distance of the robot. The efficiency model of the dynamic transform is subjected to the constraint that the geometry center of the formation must move forward in a positive direction and within a fixed range. The least square method and the Lawson algorithm are respectively adopted to solve the FEC model and the FCT model. The restricted FCT model is solved by using the Lawson algorithm and the Lagrange multiplier method. The optimal space position and the formation transform efficiency are then obtained by solving the efficiency model. The simulation shows that the proposed scheme is valid.



Published: 14 May 2010
CLC:  TP242.6  
Cite this article:

JIANG Rong-Xin, ZHANG Liang, TIAN Xiang, CHEN Yao-Wu. Optimal efficiency of multi-robot formation transform. J4, 2010, 44(4): 722-727.

URL:

http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2010.04.017     OR     http://www.zjujournals.com/eng/Y2010/V44/I4/722


多机器人队形变换最优效率求解

提出多机器人编队的队形变换最优效率求解模型.将多机器人队形变换模式分为静态变换和动态变换,选择队列变换能耗(FEC)与队列收敛时间(FCT)作为效率衡量指标.最优FEC效率模型是使得队列中所有机器人移动距离之和最小的极小模型,最优FCT效率模型是使得队列中移动距离最大的机器人的移动距离最小的极小极大模型.动态变换的效率模型增加了队形几何中心移动方向与范围的约束条件.利用最小二乘法求解FEC模型,利用Lawson算法求解FCT模型,利用Lawson算法与拉格朗日乘子法联合求解带约束的FCT模型.通过求取模型的最优解,获取各机器人变换后的最优空间位置,并得到最优的队形变换效率.仿真实验显示了该效率求解模型的有效性.

[1]  BAHCECI E, SOYSAL O, SAHIN E. A review: pattern formation and adaptation in multirobot systems [R]. Pittsburgh: Carnegie Mellon University, 2003.
[2] BARNES L, FIELDS M, VALAVANIS K. Unmanned ground vehicle swarm formation control using potential fields [C]∥ Proceedings of 2007 IEEE Mediterranean Conference on Control and Automation. Athens: IEEE, 2007: 18.
[3] SCHNEIDER F E, WILDERMUTH D. A potential field based approach to multi robot formation navigation [C]∥ Proceedings of 2003 IEEE International Conference on Robotics, Intelligent Systems and Signal Processing. Changsha: IEEE, 2003: 680685.
[4] BAZOULA A, MAAREF H. Fuzzy separation bearing control for mobile robots formation [J]. International Journal of Mechanical Systems Science and Engineering, 2007, 1(1): 1419.
[5] GILPINTO A, FRAISSE P, ZAPATA R. Decentralized strategy for carlike robot formations [C]∥ Proceedings of 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems. San Diego: IEEE/RSJ, 2007: 41764181.
[6] DESAI J P. A graph theoretic approach for modeling mobile robot team formations [J]. Journal of Robotic Systems, 2002, 19(11): 511525.
[7] HENDRICKX J M, ANDERSON B D O, DELVENNE J C, et al. Directed graphs for the analysis of rigidity and persistence in autonomous agent systems [J]. International Journal of Robust Nonlinear Control, 2007, 17: 960981.
[8] HENDRICKX J M, FIDAN B, YU C, et al. Formation reorganization by primitive operations on directed graphs [J]. IEEE Transactions on Automatic Control, 2008, 53(4): 968979.
[9] MAI C Y, LIAN F L. Analysis of formation control and communication pattern in multirobot systems [C]∥ Proceedings of SICEICASE International Joint Conference 2006. Bexco, Korea:SICEICASE, 2006: 640645.
[10] DE BERG M, VAN KREVELD M, OVERMARS M, et al. Computational geometry algorithms and applications [M]. Berlin: SpringerVerlag, 1997: 49.
[11] MOTZKIN T S, WALSH J L. Polynomials of best approximation on a real finite point set [J]. Transactions of the American Mathematical Society, 1959, 91: 231245.
[12] LAWSON C L. Contributions to the theory of linear least maximum approximations [D]. Los Angeles: University of California, 1961.

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