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The systematic method of obtaining and analyzing accurate information of a population is called data collection. A survey is a standard method of data collection that involves collecting information from a target human population about their experience, opinion, or knowledge of a product, service, or process. The responses are recorded and interpreted. The most common survey examples are written questionnaires, face-to-face or telephonic conversations, focus groups, and electronic (e-mail or...
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Robot tool use: A survey.

Meiying Qin1, Jake Brawer1, Brian Scassellati1

  • 1Yale Social Robotics Lab, Department of Computer Science, Yale University, New Haven, CT, United States.

Frontiers in Robotics and AI
|February 2, 2023
PubMed
Summary
This summary is machine-generated.

Robots can use tools to solve complex problems, requiring perception, manipulation, and cognition skills. This survey defines robot tool use and categorizes it, providing a foundation for future research and applications.

Keywords:
affordancehuman toolsmanipulationrobot tool usesurvey

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Cognitive Science

Background:

  • Robot tool use is crucial for expanding robotic capabilities in diverse applications.
  • Tool use has historically been considered a uniquely human trait, posing significant challenges for artificial systems.
  • Existing research lacks a unified framework for understanding and developing robot tool use.

Purpose of the Study:

  • To define robot tool use, identifying essential perception, manipulation, and cognition skills.
  • To establish a comprehensive taxonomy of robot tool use, drawing parallels with animal tool use.
  • To provide a theoretical foundation and practical guidelines for future robot tool use research and development.

Main Methods:

  • Defining robot tool use based on an affordance model (actions, objects, effects).
  • Compiling a taxonomy of robot tool use, categorized by task context (non-causal, causal) and complexity (single-manipulation, multiple-manipulation).
  • Reviewing existing studies within the proposed taxonomy to understand learning mechanisms.

Main Results:

  • A clear definition and taxonomy for robot tool use, distinguishing between non-causal and causal, and single- and multiple-manipulation types.
  • Identification of specific skill requirements for each sub-category of tool use.
  • Analysis of how current robot tool use studies align with the proposed framework.

Conclusions:

  • The proposed definition and taxonomy offer a foundational structure for robot tool use research.
  • Understanding the distinct skills and categorizations is key to advancing robot tool manipulation and cognition.
  • Further research is needed to address current limitations and explore broader applications of robot tool use.