HCSG combines geometric forecasting of human pose and trajectory with VLM-generated semantic descriptions of intentions, fused into a topological map with a social distance loss, yielding 14% higher success rate and 34% lower collision rate on the HA-VLNCE benchmark.
Habitat 2.0: Training home assistants to rearrange their habitat
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A primitive-based truncated diffusion model with keypoint attention encoding generates more efficient and diverse trajectories for mobile manipulators than vanilla diffusion in cluttered 3D simulations.
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HCSG: Human-Centric Semantic-Geometric Reasoning for Vision-Language Navigation
HCSG combines geometric forecasting of human pose and trajectory with VLM-generated semantic descriptions of intentions, fused into a topological map with a social distance loss, yielding 14% higher success rate and 34% lower collision rate on the HA-VLNCE benchmark.
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Primitive-based Truncated Diffusion for Efficient Trajectory Generation of Differential Drive Mobile Manipulators
A primitive-based truncated diffusion model with keypoint attention encoding generates more efficient and diverse trajectories for mobile manipulators than vanilla diffusion in cluttered 3D simulations.