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cs.RO2025
RoboScape-R: Unified Reward-Observation World Models for Generalizable Robotics Training via RL
Yinzhou Tang, Yu Shang, Yinuo Chen +8
Achieving generalizable embodied policies remains a key challenge. Traditional policy learning paradigms, including both Imitation Learning (IL) and Reinforcement Learning (RL), st…
cs.RO2025
AirScape: An Aerial Generative World Model with Motion Controllability
Baining Zhao, Rongze Tang, Mingyuan Jia +9
How to enable agents to predict the outcomes of their own motion intentions in three-dimensional space has been a fundamental problem in embodied intelligence. To explore general s…