  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. This 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 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 of 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.
