A compositional framework based on monotone co-design theory enables joint optimization of robot design, fleet composition, and planning for heterogeneous multi-robot systems under task-specific constraints.
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3 Pith papers cite this work. Polarity classification is still indexing.
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2026 3verdicts
UNVERDICTED 3representative citing papers
Explicit geometry-based feasibility supervision added to diffusion VLA training leads to better physical reliability, task success, and faster learning with limited data in manipulation tasks.
Bidirectional UGV-UAV cooperation for dynamic path planning in uncertain environments outperforms other strategies on urban road networks, with multiple UAVs providing additional travel-time reductions at increased computational expense.
citing papers explorer
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Task-Driven Co-Design of Heterogeneous Multi-Robot Systems
A compositional framework based on monotone co-design theory enables joint optimization of robot design, fleet composition, and planning for heterogeneous multi-robot systems under task-specific constraints.
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Can Explicit Physical Feasibility Benefit VLA Learning? An Empirical Study
Explicit geometry-based feasibility supervision added to diffusion VLA training leads to better physical reliability, task success, and faster learning with limited data in manipulation tasks.
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Dynamic UGV-UAV Cooperative Path Planning in Uncertain Environments
Bidirectional UGV-UAV cooperation for dynamic path planning in uncertain environments outperforms other strategies on urban road networks, with multiple UAVs providing additional travel-time reductions at increased computational expense.