发表机构
University of Science and Technology of China; Shanghai Artificial Intelligence Laboratory; Zhejiang University; Shanghai Jiaotong University; Nanjing University（中国科学技术大学; 上海人工智能实验室; 浙江大学; 上海交通大学; 南京大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出HIDE基准和SEEK框架，评估并增强部分可观测机器人操作中的技能级记忆，通过三种互补记忆机制提升任务成功率，强调内部状态表示与记忆设计匹配的重要性。
AI 中文摘要
近期机器人学习的进展使得操作策略能够执行日益多样化的任务并在不同环境中泛化。然而，可靠的执行往往依赖于无法仅从当前观测中确定的隐藏任务状态，这使得交互历史变得至关重要。我们引入了HIDE，一个用于在部分可观测性下评估操作记忆的基准。HIDE包含15个任务，涵盖重复计数、历史状态回忆和执行进度跟踪，并具有随机初始配置和决策点，在这些决策点上，相似的观测根据先前事件需要不同的动作。我们进一步提出了SEEK，一个结合三种互补记忆机制以保留历史证据并跟踪执行状态的框架。评估揭示了现有策略在HIDE上的显著局限性，而记忆增强在仿真和真实世界实验中均提高了任务成功率。单个机制对某些任务有益但可能损害其他任务；它们的组合在评估配置中在HIDE上取得了最高的平均成功率。这些发现强调了维护隐藏任务状态内部表示以及将记忆设计与任务特定信息需求相匹配的重要性。
英文摘要
Recent advances in robot learning have enabled manipulation policies to perform increasingly diverse tasks and generalize across environments. However, reliable execution often depends on hidden task states that cannot be determined from current observations alone, making interaction history essential. We introduce $HIDE$, a benchmark for evaluating manipulation memory under partial observability. HIDE comprises 15 tasks covering repetition counting, historical-state recall, and execution-progress tracking, with randomized initial configurations and decision points where similar observations require different actions depending on prior events. We further propose $SEEK$, a framework combining three complementary memory mechanisms to retain historical evidence and track execution state. Evaluations reveal substantial limitations in existing policies on HIDE, while memory augmentation improves task success in both simulation and real-world experiments. Individual mechanisms benefit some tasks but can degrade others; their combination achieves the highest average success rate on HIDE among the evaluated configurations. These findings highlight the importance of maintaining internal representations of hidden task states and matching memory design to task-specific information requirements.
CommentsProject page: https://nanamma.github.io/HIDE-SEEK/
