  Maintaining energy sufficiency of a battery-powered robot system is a
  essential for long-term missions. This capability should be flexible enough
to
  deal with different types of environment and a wide range of missions, while
  constantly guaranteeing that the robot does not run out of energy. In this
  work we present a framework based on Control Barrier Functions (CBFs) that
  provides an energy sufficiency layer that can be applied on top of any path
  planner and provides guarantees on the robot's energy consumption during
mission
  execution. In practice, we smooth the output of a generic path planner using
  double sigmoid functions and then use CBFs to ensure energy sufficiency along
  the smoothed path, for robots described by single integrator and unicycle
  kinematics. We present results using a physics-based robot simulator, as well
  as with real robots with a full localization and mapping stack to show the
  validity of our approach.

Robotics;Systems and Control;Systems and Control