A Dynamical System for Prioritizing and Coordinating Motivations
A Dynamical System for Prioritizing and Coordinating Motivations
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用于优先考虑和协调动机的动态系统
DOI：
10.1137/17m111972x
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
D. Koditschek
中科院分区：
文献类型：
--
作者：
Paul B. Reverdy;D. Koditschek
我们开发了一种动态系统方法来排序和选择多个重复任务，目的是为面临竞争目标的移动机器人提供一定程度的深思熟虑的目标选择。我们将导航作为我们的原型任务，并使用从导航函数派生的反应式(即矢量场)规划器来编码实现每个单独任务的控制策略。我们将一个标量“值”与代表其当前紧迫性的每个任务相关联，并在机器人评估其分配的任务相对于竞争任务的重要性时，让该值随时间演变。机器人的运动控制输入被生成为单个任务矢量场的凸组合。反过来，它们的权重又根据一个决策模型动态演变，该决策模型改编自关于受生物启发的群体决策的文献，由价值观驱动。在本文中，我们研究了一个具有两个重复的、相互竞争的导航任务的简单情况，并推导了保证机器人轮流重复服务的条件。具体地说，我们提供了出现稳定极限环的充分条件，机器人沿着该极限环反复交替导航到两个目标位置。数值研究表明，吸引域相当大，因此可以恢复显著的扰动，并可靠地返回到期望的任务协调模式。
We develop a dynamical systems approach to prioritizing and selecting multiple recurring tasks with the aim of conferring a degree of deliberative goal selection to a mobile robot confronted with competing objectives. We take navigation as our prototypical task, and use reactive (i.e., vector field) planners derived from navigation functions to encode control policies that achieve each individual task. We associate a scalar "value" with each task representing its current urgency and let that quantity evolve in time as the robot evaluates the importance of its assigned task relative to competing tasks. The robot's motion control input is generated as a convex combination of the individual task vector fields. Their weights, in turn, evolve dynamically according to a decision model adapted from the literature on bioinspired swarm decision making, driven by the values. In this paper we study a simple case with two recurring, competing navigation tasks and derive conditions under which it can be guaranteed that the robot will repeatedly serve each in turn. Specifically, we provide conditions sufficient for the emergence of a stable limit cycle along which the robot repeatedly and alternately navigates to the two goal locations. Numerical study suggests that the basin of attraction is quite large so that significant perturbations are recovered with a reliable return to the desired task coordination pattern.
影响因子：
4.2
作者：
Gray, Rebecca;Franci, Alessio;Leonard, Naomi Ehrich
通讯作者：
Leonard, Naomi Ehrich