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cs.RO2026
Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation
Jacob Levy, Tyler Westenbroek, Kevin Huang +6
Robot learning requires adaptation methods that improve reliably from limited, mixed-quality interaction data. This is especially challenging in long-horizon, contact-rich tasks, w…
cs.RO2025
A Player Selection Network for Scalable Game-Theoretic Prediction and Planning
Tianyu Qiu, Eric Ouano, Fernando Palafox +2
While game-theoretic planning frameworks are effective at modeling multi-agent interactions, they require solving large optimization problems where the number of variables increase…
cs.RO2023
Learning Hyperplanes for Multi-Agent Collision Avoidance in Space
Fernando Palafox, Yue Yu, David Fridovich-Keil
A core challenge of multi-robot interactions is collision avoidance among robots with potentially conflicting objectives. We propose a game-theoretic method for collision avoidance…