Beyond Action Prediction: Learning Search-Free Planning in Latent Space
[Robotyka] Autorzy: Guanchen Du, Jinhao Du, Yanpeng Sun i 3 więcej
Latent world models learn action-conditioned state transitions in a compact representation space, providing a predictive model for visual planning and control. However, planning with these models typically requires costly test-time optimization over action sequences. We propose to replace this online search with a goal-conditioned inverse model that directly predicts actions from current and goal observations. A key challenge is that action prediction alone neither ensures that goal representations encode action-relevant information nor that predicted actions are consistent with the learned latent prediction model. We introduce Hindsight Inverse JEPA Planning (HIJP), a search-free framework that addresses both aspects during training. HIJP relabels future observations along offline trajectories as goals, providing action supervision across multiple temporal horizons. By retaining gradie…
- Kategoria arxiv
- cs.RO
- Kategoria
- Robotyka