DP-GMM based probabilistic frontier prioritization enhances two multi-agent exploration algorithms with average gains of 10% and 14% in simulations across varied conditions and real dual-drone tests.
OctoMap: An efficient proba- bilistic 3D mapping framework based on octrees
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
method 1
citation-polarity summary
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2roles
method 1polarities
use method 1representative citing papers
An OctoMap frontier exploration method achieves O(number of frontiers) complexity via sensor modeling and Bayesian information gain estimation, delivering up to 54% faster exploration than standard baselines.
citing papers explorer
-
Enhancing Multi-Robot Exploration Using Probabilistic Frontier Prioritization with Dirichlet Process Gaussian Mixtures
DP-GMM based probabilistic frontier prioritization enhances two multi-agent exploration algorithms with average gains of 10% and 14% in simulations across varied conditions and real dual-drone tests.
-
Asymptotically-Bounded 3D Frontier Exploration enhanced with Bayesian Information Gain
An OctoMap frontier exploration method achieves O(number of frontiers) complexity via sensor modeling and Bayesian information gain estimation, delivering up to 54% faster exploration than standard baselines.