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机器人工具使用:一项调查。

Robot tool use: A survey.

作者信息

Qin Meiying, Brawer Jake, Scassellati Brian

机构信息

Yale Social Robotics Lab, Department of Computer Science, Yale University, New Haven, CT, United States.

出版信息

Front Robot AI. 2023 Jan 16;9:1009488. doi: 10.3389/frobt.2022.1009488. eCollection 2022.

Abstract

Using human tools can significantly benefit robots in many application domains. Such ability would allow robots to solve problems that they were unable to without tools. However, robot tool use is a challenging task. Tool use was initially considered to be the ability that distinguishes human beings from other animals. We identify three skills required for robot tool use: perception, manipulation, and high-level cognition skills. While both general manipulation tasks and tool use tasks require the same level of perception accuracy, there are unique manipulation and cognition challenges in robot tool use. In this survey, we first define robot tool use. The definition highlighted the skills required for robot tool use. The skills coincide with an affordance model which defined a three-way relation between actions, objects, and effects. We also compile a taxonomy of robot tool use with insights from animal tool use literature. Our definition and taxonomy lay a theoretical foundation for future robot tool use studies and also serve as practical guidelines for robot tool use applications. We first categorize tool use based on the context of the task. The contexts are highly similar for the same task (e.g., cutting) in , while the contexts for are diverse. We further categorize causal tool use based on the task complexity suggested in animal tool use studies into and . Single-manipulation tool use are sub-categorized based on tool features and prior experiences of tool use. This type of tool may be considered as building blocks of causal tool use. Multiple-manipulation tool use combines these building blocks in different ways. The different combinations categorize multiple-manipulation tool use. Moreover, we identify different skills required in each sub-type in the taxonomy. We then review previous studies on robot tool use based on the taxonomy and describe how the relations are learned in these studies. We conclude with a discussion of the current applications of robot tool use and open questions to address future robot tool use.

摘要

在许多应用领域中,使用人类工具能让机器人显著受益。这种能力将使机器人能够解决那些没有工具就无法解决的问题。然而,机器人使用工具是一项具有挑战性的任务。工具使用最初被认为是将人类与其他动物区分开来的能力。我们确定了机器人使用工具所需的三种技能:感知、操作和高级认知技能。虽然一般的操作任务和工具使用任务都需要相同水平的感知精度,但机器人使用工具存在独特的操作和认知挑战。在本综述中,我们首先定义机器人工具使用。该定义突出了机器人使用工具所需的技能。这些技能与一种可供性模型相契合,该模型定义了动作、物体和效果之间的三方关系。我们还结合动物工具使用文献中的见解,编制了机器人工具使用的分类法。我们的定义和分类法为未来的机器人工具使用研究奠定了理论基础,也为机器人工具使用应用提供了实用指南。我们首先根据任务背景对工具使用进行分类。对于相同任务(例如切割),不同情况下的背景高度相似,而不同任务的背景则多种多样。我们进一步根据动物工具使用研究中提出的任务复杂性,将因果工具使用分为两类。单操作工具使用根据工具特征和工具使用的先前经验进行细分。这类工具可被视为因果工具使用的构建模块。多操作工具使用以不同方式组合这些构建模块。不同的组合对多操作工具使用进行分类。此外,我们确定了分类法中每个子类型所需的不同技能。然后,我们根据分类法回顾先前关于机器人工具使用的研究,并描述在这些研究中如何学习这些关系。我们最后讨论了机器人工具使用的当前应用以及有待解决的未来机器人工具使用的开放性问题。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d3eb/9885045/f43886540475/frobt-09-1009488-g001.jpg

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