In this paper, we address the problem of safe trajectory planning for
autonomous search and exploration in constrained, cluttered environments.
Guaranteeing safe navigation is a challenging problem that has garnered
significant attention. This work contributes a method that generates guaranteed
safety-critical search trajectories in a cluttered environment. Our approach
integrates safety-critical constraints using discrete control barrier functions
(DCBFs) with ergodic trajectory optimization to enable safe exploration.
Ergodic trajectory optimization plans continuous exploratory trajectories that
guarantee full coverage of a space. We demonstrate through simulated and
experimental results on a drone that our approach is able to generate
trajectories that enable safe and effective exploration. Furthermore, we show
the efficacy of our approach for safe exploration of real-world single- and
multi- drone platforms.