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Toward a framework for levels of robot autonomy in human-robot interaction
Jenay M Beer1, Arthur D Fisk1, Wendy A Rogers1
1School of Psychology, Georgia Institute of Technology.
Journal of Human-Robot Interaction
|October 31, 2017
Summary
This study introduces a framework for understanding human-robot interaction (HRI) by defining levels of robot autonomy (LORA). It categorizes robot autonomy on a 10-point scale to guide HRI research.
Area of Science:
- Robotics
- Human-Computer Interaction
- Artificial Intelligence
Background:
- Autonomy is a critical factor in human-robot interaction (HRI), with varying levels across robot platforms.
- Understanding the influence of robot autonomy on HRI is essential for designing effective human-robot systems.
- Existing research in human-automation interaction provides a foundation for studying human-related variables in HRI.
Purpose of the Study:
- To develop a comprehensive framework for levels of robot autonomy (LORA) within the context of HRI.
- To redefine the construct of autonomy specifically for HRI applications.
- To establish guidelines for categorizing robot autonomy and understanding its impact on HRI variables.
Main Methods:
- Reviewing and redefining the concept of autonomy in HRI.
- Developing a 10-point taxonomy to categorize levels of robot autonomy.
- Linking HRI principles with established human-automation interaction methodologies.
Main Results:
- A proposed framework for levels of robot autonomy in HRI.
- A 10-point qualitative taxonomy for classifying robot autonomy.
- Identification of key HRI variables influenced by LORA, such as acceptance, situation awareness, and reliability.
Conclusions:
- The developed framework provides a structured approach to understanding and quantifying robot autonomy in HRI.
- The LORA taxonomy offers a standardized method for categorizing robot autonomy levels.
- This work facilitates further research into the relationship between robot autonomy and critical HRI outcomes.
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