25 research outputs found
Safety-Critical Ergodic Exploration in Cluttered Environments via Control Barrier Functions
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
Energy-Aware Ergodic Search: Continuous Exploration for Multi-Agent Systems with Battery Constraints
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.Comment: 7 pages, 7 figures, ICRA'2