Scout-Assisted Planning uses UAV scouts and a GNN to predict information gain for pruning actions, cutting UGV travel costs by 31.9-37.7% versus the Canadian Traveler Problem baseline in partially known environments.
Advances in neural information processing systems , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Optimizing trajectory-trees in belief space improves performance in partially observable robotic planning by capturing observation-dependent contingencies, shown via PO-MPC with D-AuLa optimization and PO-LGP extending LGP.
citing papers explorer
-
Scout-Assisted Planning for Heterogeneous Robot Teams under Partially Known Environments
Scout-Assisted Planning uses UAV scouts and a GNN to predict information gain for pruning actions, cutting UGV travel costs by 31.9-37.7% versus the Canadian Traveler Problem baseline in partially known environments.
-
Optimizing Trajectory-Trees in Belief Space: An Application from Model Predictive Control to Task and Motion Planning
Optimizing trajectory-trees in belief space improves performance in partially observable robotic planning by capturing observation-dependent contingencies, shown via PO-MPC with D-AuLa optimization and PO-LGP extending LGP.