MaP-WAM tackles non-Markovian robot manipulation with memory-grounded planning
Sizhe Zhao · hf · 2026-09-11
Researchers propose MaP-WAM (Memory as Plans), a world-action model for non-Markovian robotic manipulation that decouples memory-grounded planning from plan-conditioned execution.
- Uses compact episodic segment records as the memory substrate for planning
- Executes via progress-calibrated action chunks
- Maintains fixed inference latency regardless of memory length
The approach improves performance on long-horizon, history-dependent manipulation tasks.
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