CoFL learns continuous flow fields from BEV images and language instructions to generate navigation trajectories, outperforming modular VLM planners and trajectory policies on unseen scenes.
Graph-based subterranean exploration path planning using aerial and legged robots,
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COMPASS is a manipulation-aware active sensing framework that raises simulated manipulation success rates by 24.25% over information-gain-only baselines in a new four-level confined-space benchmark.
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CoFL: Continuous Flow Fields for Language-Conditioned Navigation
CoFL learns continuous flow fields from BEV images and language instructions to generate navigation trajectories, outperforming modular VLM planners and trajectory policies on unseen scenes.
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COMPASS: Confined-space Manipulation Planning with Active Sensing Strategy
COMPASS is a manipulation-aware active sensing framework that raises simulated manipulation success rates by 24.25% over information-gain-only baselines in a new four-level confined-space benchmark.