2 papers
cs.RO2026
Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation
Tyler Han, Bat Nemekhbold, Siyang Shen +6
Current methods in robot learning are fundamentally bottlenecked by one or more of: hand-designed rewards, simulation modeling, or action supervision (e.g. teleoperation) each requ…
cs.RO2025
Long Range Navigator (LRN): Extending robot planning horizons beyond metric maps
Matt Schmittle, Rohan Baijal, Nathan Hatch +6
A robot navigating an outdoor environment with no prior knowledge of the space must rely on its local sensing to perceive its surroundings and plan. This can come in the form of a…