MAGICIAN uses Imagined Gaussians from occupancy networks for efficient coverage gain computation in tree-search based long-horizon planning for active mapping, achieving SOTA results on indoor and outdoor benchmarks.
Rapidly-exploring random trees: A new tool for path planning.Research Report 9811, 1998
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RoboAgent chains basic vision-language capabilities inside a single VLM via a scheduler and trains it in three stages (behavior cloning, DAgger, RL) to improve embodied task planning.
citing papers explorer
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MAGICIAN: Efficient Long-Term Planning with Imagined Gaussians for Active Mapping
MAGICIAN uses Imagined Gaussians from occupancy networks for efficient coverage gain computation in tree-search based long-horizon planning for active mapping, achieving SOTA results on indoor and outdoor benchmarks.
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RoboAgent: Chaining Basic Capabilities for Embodied Task Planning
RoboAgent chains basic vision-language capabilities inside a single VLM via a scheduler and trains it in three stages (behavior cloning, DAgger, RL) to improve embodied task planning.