Coordination of control in robot teams using game-theoretic learning
Coordination of control in robot teams using game-theoretic learning
复制标题
使用博弈论学习协调机器人团队的控制
DOI：
10.3182/20140824-6-za-1003.02504
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
S. Veres
中科院分区：
文献类型：
--
作者：
M. Smyrnakis;S. Veres
摘要 本文提出了一种分布式决策方法来解决机器人团队成员的控制工作分配问题。目标是让一组自主机器人协调其行动，以有效地完成任务。提出了一种新颖的控制器设计方法，该方法允许机器人团队基于使用虚拟游戏和扩展卡尔曼滤波器的博弈论学习算法进行协作。特别是，团队中的每个机器人都会预测其他机器人的计划行动，同时做出决定以最大化自己的预期奖励，该奖励取决于联合成功完成任务的奖励。经过理论分析，在仓库中物料搬运和巡逻机器人之间的协作场景中测试了所提出算法的性能。
Abstract This paper presents a distributed decision making approach to the problem of control effort allocation to robotic team members. The objective is for a team of autonomous robots to coordinate their actions in order to efficiently complete a task. A novel controller design methodology is proposed which allows the robot team to work together based on a gametheoretic learning algorithms using fictitious play and extended Kalman filters. In particular each robot of the team predicts the other robots' planned actions while making decision to maximise its own expected reward that is dependent on the reward for joint successful completion of the task. After theoretical analysis the performance of the proposed algorithm is tested on a scenario of collaboration between material handling and patrolling robots in a warehouse.
理性智能体自主小行星探索
影响因子：
9
作者：
Lincoln N
通讯作者：
Lincoln N