arXiv cs.AI· Siqi Li, Ziyi Bai, Xinrun Xu, Tinglei Huang, B\"orje F. Karlsson·· 11 小时前AI 评分31
当过去塑造行动：理解具身记忆
When the Past Shapes Action: Understanding Embodied Memory
AI 导读
一篇综述将具身记忆定义为在当前离线观察之外保留决策相关信息的能力，并按六大记忆需求与八类架构（循环状态、fast weights、视觉与符号表示、空间记忆、经验型系统等）梳理现有方法。文章还分析了现有 benchmark 如何区分真正使用历史信息与一般任务表现，并指出选择相关经验、在变化环境中维持一致信念、跨 episode 巩固知识等开放挑战。
正文 · 原文
Abstract:Recent advances in generative foundation models have expanded the capabilities of embodied AI, enabling increasingly general navigation, manipulation, and long-horizon task execution. However, effective interaction with dynamic environments requires more than only strong perception and reasoning: agents must act with partial knowledge and retain, retrieve, and update information from past observations, actions, and experiences. This survey examines embodied memory as a mechanism for preserving decision-relevant information beyond the current observation. We organize existing approaches along two complementary dimensions: six fundamental memory requirements, spanning world-state persistence, task progress, belief maintenance, and experiential learning; and eight architectural categories, including recurrent states, fast weights, visual and symbolic representations, spatial memory, and experience-based systems. We analyze their capabilities and limitations, and examine how existing benchmarks evaluate memory-dependent behavior, distinguishing genuine use of historical information from general task performance. Finally, we identify open challenges in selecting relevant experiences, maintaining consistent beliefs in changing environments, and consolidating knowledge across episodes. Our analysis provides a framework for understanding memory as an essential component of reliable, adaptive, and lifelong-horizon embodied intelligence.
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2610.41688 [cs.RO] |
| (or arXiv:2610.41688v1 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2610.41688 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Börje F. Karlsson [view email]
[v1]
Fri, 30 Oct 2026 12:52:37 UTC (3,532 KB)
来源：arXiv cs.AI · arxiv.org