Fixed-size episodic memory improves robot success on history-dependent tasks

single source· 1 articles · confidence: medium · first seen 2026-09-22 20:00 UTC

What this means for you

Nothing to act on yet. This is a preprint: no code or weights are mentioned, and the numbers are the authors' own runs on RMBench and LIBERO-Long. If you train robot policies on tasks that depend on earlier observations, the design is worth copying — a fixed-size memory rather than an ever-growing context.

An arXiv preprint dated 22 September describes MemBodied, a fixed-size episodic memory for robot policies — vision-language-action models that turn images and instructions into movement. Instead of keeping past observations in context, it carries an associative state across policy calls plus a compressed version of the opening scene. On five RMBench tasks requiring memory, the authors report 7.81 times the mean success rate of a stateless policy, 2.98 times a vanilla recurrent memory, and 1.3 times the strongest memory-augmented baseline with ten times fewer added parameters. On LIBERO-Long it reports 90.6%, 5.4% above the stateless π0 policy. No evaluation date is given and the paper is not peer reviewed.

Key facts

  • ·MemBodied is described as a fixed-size episodic memory with two components: an associative state recording interactions across policy calls, and an episode anchor preserving a compact representation of the initial scene. source
  • ·Across five RMBench tasks requiring memory, the authors report 7.81 times the mean success rate of a stateless policy and 2.98 times that of vanilla recurrent memory. source
  • ·The method is reported to outperform the strongest memory-augmented baseline by 1.3 times while adding ten times fewer parameters. source
  • ·On the LIBERO-Long suite it reports 90.6%, described as a 5.4% improvement over the stateless π0 policy. source
  • ·The work is an arXiv preprint (2609.28256) dated 22 September 2026; no evaluation date is given for the reported scores. source

What the sources say

Sources

The original reporting. Follow these — they did the work.

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