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Autonomous 3D Exploration in Large-Scale Environments with Dynamic Obstacles
DAEP outperform state-of-the-art planners in dynamic and large-scale environments.
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms
This paper presents preliminary work on using deep neural networks to guide general-purpose heuristic algorithms for performing utilitarian combinatorial assignment.
Enhancing Lattice-based Motion Planning with Introspective Learning and Reasoning
Reasoning takes place to both verify that the learned models stays safe and to improve collision checking effectiveness in the motion planner by the use of more accurate execution predictions with a smaller safety margin.
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