arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2006.13171cs.CVcs.RO

ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects

Facebook AI Research(Facebook 人工智能研究院);Georgia Institute of Technology(佐治亚理工学院);Allen Institute for Artificial Intelligence(艾伦人工智能研究所);Simon Fraser University(西蒙弗雷泽大学);Robotics at Google(谷歌机器人部门)

Dhruv Batra, Aaron Gokaslan, Aniruddha Kembhavi, Oleksandr Maksymets, Roozbeh Mottaghi, Manolis Savva, Alexander Toshev, Erik Wijmans

英文摘要:

We revisit the problem of Object-Goal Navigation (ObjectNav). In its simplest form, ObjectNav is defined as the task of navigating to an object, specified by its label, in an unexplored environment. In particular, the agent is initialized at a random location and pose in an environment and asked to find an instance of an object category, e.g., find a chair, by navigating to it. As the community begins to show increased interest in semantic goal specification for navigation tasks, a number of different often-inconsistent interpretations of this task are emerging. This document summarizes the consensus recommendations of this working group on ObjectNav. In particular, we make recommendations on subtle but important details of evaluation criteria (for measuring success when navigating towards a target object), the agent's embodiment parameters, and the characteristics of the environments within which the task is carried out. Finally, we provide a detailed description of the instantiation of these recommendations in challenges organized at the Embodied AI workshop at CVPR 2020 http://embodied-ai.org .

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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