Neural Motion Simulator Pushing the Limit of World Models in Reinforcement Learning
Chenjie Hao, Weyl Lu, Yifan Xu, Yubei Chen
2025年份
2顶会引用
摘要
Figure 1. This figure demonstrate the long-horizon precise prediction by the Neural Motion Simulators. In each of the three pictures, the first row shows the ground-truth states and the second row shows the predicted states with the same initial condition and actions sequence. Humanoid predicts for 30 steps with rendering every 3 steps; Panda predicts for 200 steps with rendering every 20 steps; myohand predicts for 400 steps with rendering every 40 steps.
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