Robotics Software Engineering: A Perspective from the Service Robotics Domain
Not on the map. Why?
Abstract (arXiv)
Robots that support humans by performing useful tasks (a.k.a., service robots) are booming worldwide. In contrast to industrial robots, the development of service robots comes with severe software engineering challenges, since they require high levels of robustness and autonomy to operate in highly heterogeneous environments. As a domain with critical safety implications, service robotics faces a need for sound software development practices. In this paper, we present the first large-scale empirical study to assess the state of the art and practice of robotics software engineering. We conducted 18 semi-structured interviews with industrial practitioners working in 15 companies from 9 different countries and a survey with 156 respondents (from 26 countries) from the robotics domain. Our results provide a comprehensive picture of (i) the practices applied by robotics industrial and academic practitioners, including processes, paradigms, languages, tools, frameworks, and reuse practices, (ii) the distinguishing characteristics of robotics software engineering, and (iii) recurrent challenges usually faced, together with adopted solutions. The paper concludes by discussing observations, derived hypotheses, and proposed actions for researchers and practitioners.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Jun 2020.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 2; 2026: 1.
6 papers.
- 2021Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systemscited by 36
- 2023Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testingcited by 8
- 2026AEROS: A Single-Agent Operating Architecture with Embodied Capability Modulescited by 6
- 2025Simulator Ensembles for Trustworthy Autonomous Driving Systems Testingcited by 1
- 2025A Multi-Modality Evaluation of the Reality Gap in Autonomous Driving Systemscited by 1
- 2022Cloud Native Robotic Applications with GPU Sharing on Kubernetescited by 0
- 2026AEROS: A Single-Agent Operating Architecture with Embodied Capability Modules8 Apr 2026
- 2025A Multi-Modality Evaluation of the Reality Gap in Autonomous Driving Systems26 Sep 2025
- 2025Simulator Ensembles for Trustworthy Autonomous Driving Systems Testing11 Mar 2025
- 2023Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing14 May 2023
- 2022Cloud Native Robotic Applications with GPU Sharing on Kubernetes8 Oct 2022
- 2021Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems21 Dec 2021