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• W4386136919 endingPage "18" @default.
• W4386136919 startingPage "1" @default.
• W4386136919 abstract "Humans perform everyday tasks using a combination of locomotion and manipulation skills. Building a system that can handle both skills is essential to creating virtual humans. We present a physically-simulated human capable of solving box rearrangement tasks, which requires a combination of both skills. We propose a hierarchical control architecture, where each level solves the task at a different level of abstraction, and the result is a physics-based simulated virtual human capable of rearranging boxes in a cluttered environment. The control architecture integrates a planner, diffusion models, and physics-based motion imitation of sparse motion clips using deep reinforcement learning. Boxes can vary in size, weight, shape, and placement height. Code and trained control policies are provided." @default.
• W4386136919 created "2023-08-25" @default.
• W4386136919 creator A5022699565 @default.
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• W4386136919 date "2023-08-16" @default.
• W4386136919 modified "2023-10-01" @default.
• W4386136919 title "Hierarchical Planning and Control for Box Loco-Manipulation" @default.
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• W4386136919 doi "https://doi.org/10.1145/3606931" @default.
• W4386136919 hasPublicationYear "2023" @default.
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