  Continuous exploration without interruption is important in scenarios such as
search and rescue and precision agriculture, where consistent presence is
needed to detect events over large areas. Ergodic search already derives
continuous trajectories in these scenarios so that a robot spends more time in
areas with high information density. However, existing literature on ergodic
search does not consider the robot's energy constraints, limiting how long a
robot can explore. In fact, if the robots are battery-powered, it is physically
not possible to continuously explore on a single battery charge. Our paper
tackles this challenge, integrating ergodic search methods with energy-aware
coverage. We trade off battery usage and coverage quality, maintaining
uninterrupted exploration by at least one agent. Our approach derives an
abstract battery model for future state-of-charge estimation and extends
canonical ergodic search to ergodic search under battery constraints. Empirical
data from simulations and real-world experiments demonstrate the effectiveness
of our energy-aware ergodic search, which ensures continuous exploration and
guarantees spatial coverage.
