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cs.RO2026
Flow Policies as Actions of Skill-Level World Models: Learned and Symbolic Abstractions for Long-Horizon Planning
Andreu Matoses Gimenez, Andrei-Carlo Papuc, Chris Pek +1
Latent world models enable robots to plan by predicting the consequences of actions. Planning long tasks with control-rate actions requires many prediction steps, which enlarges th…
cs.RO2026
Strategizing at Speed: A Learned Model Predictive Game for Multi-Agent Drone Racing
Andrei-Carlo Papuc, Lasse Peters, Sihao Sun +2
Autonomous drone racing pushes the boundaries of high-speed motion planning and multi-agent strategic decision-making. Success in this domain requires drones not only to navigate a…