From Sliding Windows to Self-evolving Lifelong Memory: A Dual-perspective Survey of Memory Paradigms for Long-Horizon Robotics VLA Models

Key points

• As a result, memory has become a fundamental component for enabling embodied agents to perform long-horizon reasoning and adaptive decision-making.1
• This survey presents a systematic taxonomy of VLA memory mechanisms based on memory scope and persistence, categorizing existing approaches into five representative paradigms and one emerging frontier.1
• Finally, we discuss the key challenges in building full-lifecycle memory systems, including efficient memory management and lifelong knowledge evolu-tion.1
• Overall, this survey provides a unified perspective on memory architectures for VLA agents and offers insights into the development of lifelong embodied in-telligence.1

Sources (1)

• [1]From Sliding Windows to Self-evolving Lifelong Memory: A Dual-perspective Survey of Memory Paradigms for Long-Horizon Robotics VLA Models
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 16, 11:23 AM

  Long-horizon robotic tasks expose a fundamental limitation of current Vision-Language-Action (VLA) models because their restricted temporal context pre-vents effective accumulation and reuse of past experiences.

  As a result, memory has become a fundamental component for enabling embodied agents to perform long-horizon reasoning and adaptive decision-making.

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