Preprint
Nov 2026
ODE Policy: Robot Learning via Action Dynamics, Not Actions
Most robot policies, whether trained by imitation learning (IL) or reinforcement learning (RL), map observations to action values at discrete control steps and leave the continuity of physical motion to be learned implicitly. We propose ODE policy, which learns the dynamics of the action rather than the action itself....
Jin-Dou Jia, Jing-Liang Li, Kuang-Ji Zuo et al.
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