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Control of Soccer Robots Using Behaviour Trees

机译:使用行为树控制足球机器人

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In the paper a novel behaviour tree based control used in decision making processes of robot soccer is proposed. Decision Making (DM) is a basic block of robot that analyses the current state of world model and makes decision about new positions of robots. Proposed behaviour tree (BT) has high and low level behaviours and its nodes are operating using certain behaviour rules given in the paper. High level behaviours are implemented using low level behaviours. The new behaviours of soccer robots are designed using tree structure. The use of BT approach allows to model complicated situations easily that show advantages of this technique over finite state machines widely used in robot control. After defining behaviours and making decisions, path finding module determines the path of robot. In the paper the integration of a Rapidly Exploring Random Tree (RRT) with path smoothing techniques is developed to find the path of the robot in a short time. The obtained simulation and experimental results show that the constructed navigation system of soccer robots efficiently finds desirable and feasible solutions in short amount of time.
机译:在论文中,提出了一种用于决策过程的基于新的行为树控制机器人足球的过程。决策(DM)是分析世界模型的当前状态的基本机器人,并决定机器人的新位置。建议的行为树(BT)具有高,​​低级别行为,其节点正在使用纸张中给出的某些行为规则进行操作。使用低级行为实现高级行为。足球机器人的新行为使用树结构设计。 BT方法的使用允许更容易地模拟复杂的情况,显示出该技术的优势在机器人控制中广泛使用的有限状态机器上。在定义行为和制定决策后,路径查找模块确定机器人的路径。在论文中,开发了一种快速探索随机树(RRT)与路径平滑技术,以在短时间内找到机器人的路径。获得的模拟和实验结果表明,足球机器人的构建导航系统有效地在短时间内找到了所需和可行的解决方案。

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