Flow-Opt combines a flow-matching DiT model with a custom differentiable safety filter and learned initialization to enable fast centralized trajectory optimization for tens of robots.
Interactive joint planning for autonomous vehicles
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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cs.RO 2years
2025 2verdicts
UNVERDICTED 2representative citing papers
A contingency planning method for autonomous vehicles that learns human vehicle uncertainties online and uses reachable set barriers for non-conservative safety.
citing papers explorer
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Flow-Opt: Scalable Centralized Multi-Robot Trajectory Optimization with Flow Matching and Differentiable Optimization
Flow-Opt combines a flow-matching DiT model with a custom differentiable safety filter and learned initialization to enable fast centralized trajectory optimization for tens of robots.
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Safe and Nonconservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers
A contingency planning method for autonomous vehicles that learns human vehicle uncertainties online and uses reachable set barriers for non-conservative safety.