Persistification of Robotic Tasks
Persistification of Robotic Tasks
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DOI：
10.1109/tcst.2020.2978913
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发表时间：
2021-03-01
影响因子：
4.8
通讯作者：
Egerstedt, Magnus
中科院分区：
文献类型：
--
作者：
Notomista, Gennaro;Egerstedt, Magnus
在本文中，我们提出了一个控制框架，使机器人能够持久地执行任务，即在比机器人电池寿命长得多的时间范围内执行任务。这是通过确保机器人电池中储存的能量永远不会耗尽来实现的。这个条件被定义为优化问题中的一组不变性约束，优化问题的目标是最小化机器人的控制输入和对应于要执行的任务的标称控制输入之间的差异。我们把这个过程称为机器人任务的持久化。利用控制障碍函数将机器人状态空间子集的前向不变性转化为控制输入约束。对能量约束下的优化问题的求解保证了机器人任务的持续性。为了说明所提议的框架的运作，我们考虑了两个任务，它们的持续执行是特别相关的：环境勘探和环境监测。我们展示了这两项任务在模拟和一队轮式移动机器人在机器人馆的持久性。
In this article, we propose a control framework that enables robots to execute tasks persistently, i.e., over time horizons much longer than robots' battery life. This is achieved by ensuring that the energy stored in the batteries of the robots is never depleted. This condition is framed as a set invariance constraint in an optimization problem whose objective is that to minimize the difference between the robots' control inputs and nominal control inputs corresponding to the task that is to be executed. We refer to this process as the persistification of a robotic task. Forward invariance of subsets of the state space of the robots is turned into a control input constraint by using control barrier functions. The solution to the formulated optimization problem with energy constraints ensures that the robotic task is persistent. To illustrate the operation of the proposed framework, we consider two tasks whose persistent execution is particularly relevant: environment exploration and environment surveillance. We show the persistification of these two tasks both in simulation and on a team of wheeled mobile robots on the Robotarium.