Capability-based Frameworks for Industrial Robot Skills: a Survey

TL;DR

This survey analyzes 210 papers to identify common frameworks for robot skills, emphasizing a task-skill-primitive taxonomy and highlighting the need for industrial-specific research on parametric capabilities and safety.

Contribution

It provides a structured review of robot skill frameworks, proposing a standardized taxonomy and identifying gaps in industrial applications, especially for parametric capabilities.

Findings

Most research agrees on a task-skill-primitive taxonomy.

Pick and place are the most studied capabilities.

Industrial applications focus on simple, fixed-parameter capabilities with safety considerations.

Abstract

The research community is puzzled with words like skill, action, atomic unit and others when describing robots' capabilities. However, for giving the possibility to integrate capabilities in industrial scenarios, a standardization of these descriptions is necessary. This work uses a structured review approach to identify commonalities and differences in the research community of robots' skill frameworks. Through this method, 210 papers were analyzed and three main results were obtained. First, the vast majority of authors agree on a taxonomy based on task, skill and primitive. Second, the most investigated robots' capabilities are pick and place. Third, industrial oriented applications focus more on simple robots' capabilities with fixed parameters while ensuring safety aspects. Therefore, this work emphasizes that a taxonomy based on task, skill and primitives should be used by future works to align with existing literature. Moreover, further research is needed in the industrial domain for parametric robots' capabilities while ensuring safety.