A networked formation control for groups of mobile robots using mixed integer programming

A networked formation control for groups of mobile robots using mixed integer programming
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使用混合整数规划的移动机器人组的网络编队控制

DOI:
10.1109/cacsd-cca-isic.2006.4776710
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发表时间:
2006
期刊:
2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control
影响因子:
--
通讯作者:
Oliver Sawodny
Oliver Sawodny
中科院分区:
--
文献类型:
--
作者:
T. Kopfstedt;Masakazu Mukai;Masayuki Fujita;Oliver Sawodny

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在本文中,我们展示了一种有效的方式来描述和控制网络控制的移动的机器人编队使用最小化机器人间的通信。因此,我们采用全局集中式规划算法,通过混合整数二次规划(MIQP)求解移动的机器人编队的最优轨迹问题。编队的这种描述可以用于非静态编队以及用于不同种类的编队之间的编队切换,其中机器人间的碰撞将被避免,并且编队被组织为单元中心参考编队。环境本身可以由被描述为混合系统的凸多边形来表示。沿着最佳轨迹的沿着移动由三个级别的控制器结构控制,其中最高级别被设置在主机器人上,并且使用机器人之间的蓝牙通信来控制一般编队。每个机器人的位置控制由每个机器人上的单独控制器和每个机器人的每个轮子的电机控制器来实现。仿真和实验验证了所提出的编队控制结构和轨迹规划算法的有效性,并验证了机器人的动力学模型
In this paper we demonstrate an effective way of description and control for network-controlled formations of mobile robots using minimized inter-robot communication. Therefore we use a global centralized planning algorithm and solve the optimal trajectory problem of the formation of mobile robots by mixed integer quadratic programming (MIQP). This description of formation can be used for non-static formations as well as for formation switching between different kinds of formations where inter-robot collisions will be avoided and the formations are organized as unit-center-referenced formations. The environment itself can be formulated by convex polygons that are described as hybrid systems. The moving along the optimum trajectories is controlled by a controller structure in three levels, whereby the highest level is set on a master robot and controls the general formation using Bluetooth communication between the robots. The control of the position of each robot is realized by an individual controller on every robot and a motor controller for every wheel of each robot. The effectiveness of our formation control structure and the algorithm for the planning of the trajectory is demonstrated in simulations and experiments which also verify the dynamic models of the robots