发表机构
Peking University（北京大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对具身任务规划中模拟器和数据集孤立的问题，提出UniETP统一接口，整合四个常用模拟器，兼具标准化与多样性，构建新数据集，通过实验评估模型具身规划能力并分析瓶颈。
AI 中文摘要
本文聚焦具身任务规划问题，即智能体需在交互环境中执行一系列原子动作以完成用户指定任务。此前虽有多种模拟器和数据集，但相互孤立。为此提出UniETP，它整合了四个常用模拟器。其特点是标准化与多样性兼具，一方面规范观察和动作空间并构建评估系统，另一方面提升任务多样性和复杂性，自动构建新数据集。通过实验评估模型具身规划能力并分析瓶颈。
英文摘要
This paper focuses on the problem of Embodied Task Planning, where an agent is required to execute a sequence of atomic actions within an interactive environment to complete a user-specified task. Though a variety of simulators and datasets have previously been built for this task, these efforts are largely isolated, with each using its own observation format, action type, and task domain. This fragmentation complicates comprehensive model evaluation and hinders the scalability of training data. As an effort towards generalizable embodied planning, we propose UniETP, a unified interface integrating four commonly-used simulators (AI2-THOR, VirtualHome, Habitat, BEHAVIOR). UniETP is characterized by both standardization and diversity. On one hand, it formalizes all the simulators into a consistent observation and action space, and builds an evaluation system to support complicated task goal. On the other hand, it enhances task diversity and complexity across dimensions like task logic, instance grounding, and instruction understanding, constructing a new dataset with varied levels of difficulty in an automatic manner. Extensive experiments on the proposed benchmark are conducted to evaluate the embodied planning capabilities of recent models and analyze the performance bottlenecks. Codes and data will be available at https://github.com/woyut/UniETP .
CommentsWe are actively working on releasing the codes and data
