Abstract
In this paper we propose a control framework that enables robots to execute tasks persistently, i. e., over time horizons much longer than robots' battery life, which is achieved by ensuring that the energy stored in the batteries of the robots is never depleted. This is framed as a set invariance constraint in an optimization problem whose objective is that of minimizing the distance 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 of the formulated optimization problem with energy constraints ensures that the resulting 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.
Abstract (translated)
在本文中，我们提出了一个控制框架，使机器人能够持续执行任务，即，随着时间的推移，比机器人的电池寿命长得多，这是通过确保存储在机器人电池中的能量永不耗尽来实现的。在优化问题中，这是一个集合不变性约束，其目标是使机器人的控制输入和要执行的任务对应的名义控制输入之间的距离最小化。我们将此过程称为机器人任务的持久化。利用控制屏障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。能量约束下的优化问题的求解，保证了所得到的任务是持久的。为了说明拟议框架的运作，我们考虑了两个持续执行特别相关的任务：环境勘探和环境监测。我们展示了这两个任务的持续性，无论是在模拟和一组轮式移动机器人上的机器人。
URL
https://arxiv.org/abs/1903.05810
