Software Reconfiguration in Robotics

TL;DR

This paper surveys the landscape of software reconfiguration in robotics, analyzing academic research, practical frameworks, and real systems to identify gaps and guide future development of effective, adoptable reconfiguration techniques.

Contribution

It provides a comprehensive analysis of reconfiguration techniques, frameworks, and systems, highlighting discrepancies between research focus and practical usage in robotics.

Findings

Parameter reconfiguration dominates practical use

Research emphasizes structural reconfiguration, less adopted in practice

Significant gaps identified between research and real-world application

Abstract

Robots often need to be reconfigurable$-$to customize, calibrate, or optimize robots operating in varying environments with different hardware). A particular challenge in robotics is the automated and dynamic reconfiguration to load and unload software components, as well as parameterizing them. Over the last decades, a large variety of software reconfiguration techniques has been presented in the literature, many specifically for robotics systems. Also many robotics frameworks support reconfiguration. Unfortunately, there is a lack of empirical data on the actual use of reconfiguration techniques in real robotics projects and on their realization in robotics frameworks. To advance reconfiguration techniques and support their adoption, we need to improve our empirical understanding of them in practice. We present a study of automated reconfiguration at runtime in the robotics domain. We determine the state-of-the art by reviewing 78 relevant publications on reconfiguration. We determine the state-of-practice by analyzing how four major robotics frameworks support reconfiguration, and how reconfiguration is realized in 48 robotics (sub-)systems. We contribute a detailed analysis of the design space of reconfiguration techniques. We identify trends and research gaps. Our results show a significant discrepancy between the state-of-the-art and the state-of-practice. While the scientific community focuses on complex structural reconfiguration, only parameter reconfiguration is widely used in practice. Our results support practitioners to realize reconfiguration in robotics systems, as well as they support researchers and tool builders to create more effective reconfiguration techniques that are adopted in practice.