Software Engineering for Robotic Systems:a systematic mapping study

TL;DR

This systematic mapping study reviews 50 research papers to analyze how software engineering techniques are applied in robotic systems, highlighting current trends, gaps, and future research opportunities in the field.

Contribution

It provides a comprehensive classification of software engineering approaches used in robotics, based on the SWEBOK guide, and identifies research gaps in testing and quality assurance.

Findings

Most studies focus on development phases like design and construction.

Testing and quality assurance are underrepresented in current research.

Identified five software engineering areas applied in robotic systems.

Abstract

Robots are being applied in a vast range of fields, leading researchers and practitioners to write tasks more complex than in the past. The robot software complexity increases the difficulty of engineering the robot's software components with quality requirements. Researchers and practitioners have applied software engineering (SE) approaches and robotic domains to address this issue in the last two decades. This study aims to identify, classify and evaluate the current state-of-the-art Software Engineering for Robotic Systems (SERS). We systematically selected and analyzed 50 primary studies extracted from an automated search on Scopus digital library and manual search on the two editions of the RoSE workshop. We present three main contributions. Firstly, we provide an analysis from three following perspectives: demographics of publication, SE areas applied in robotics domains, and RSE findings. Secondly, we show a catalogue of research studies that apply software engineering techniques in the robotic domain, classified with the SWEBOK guide. We have identified 5 of 15 software engineering areas from the SWEBOK guide applied explicitly in robotic domains. The majority of the studies focused on the development phase (design, models and methods and construction). Testing and quality software areas have little coverage in SERS. Finally, we identify research opportunities and gaps in software engineering for robotic systems for future studies.