Software Engineering for Robotics: Future Research Directions; Report from the 2023 Workshop on Software Engineering for Robotics

TL;DR

Robotics software engineering faces unique challenges due to deployment in uncertain physical environments, human-robot interactions, simulation-reality gaps, heterogeneous layered architectures, integration of learned components, scalability, and siloed development. The paper reports on an NSF-sponsored 2023 workshop that identifies seven key challenges and maps them to seven near-term research directions, including modern resource abstractions, multi-view ADLs, HRI processes, massive simulation ecosystems, multi-dimensional QA, evidence-based assurances, and robotics-focused curricula. The proposed agenda emphasizes middleware design, cross-disciplinary modelling, large-scale simulation collaboration, robust QA and assurance frameworks, and federated education to accelerate safe, scalable robot deployments. Collectively, the work provides a roadmap to unify software engineering practices for robotics, aiming to improve safety, reliability, interoperability, and adoption across industry, research, and government. The outcomes stress community-building and sustained funding as critical enablers for realizing the proposed SE-for-robotics vision.

Abstract

Robots are experiencing a revolution as they permeate many aspects of our daily lives, from performing house maintenance to infrastructure inspection, from efficiently warehousing goods to autonomous vehicles, and more. This technical progress and its impact are astounding. This revolution, however, is outstripping the capabilities of existing software development processes, techniques, and tools, which largely have remained unchanged for decades. These capabilities are ill-suited to handling the challenges unique to robotics software such as dealing with a wide diversity of domains, heterogeneous hardware, programmed and learned components, complex physical environments captured and modeled with uncertainty, emergent behaviors that include human interactions, and scalability demands that span across multiple dimensions. Looking ahead to the need to develop software for robots that are ever more ubiquitous, autonomous, and reliant on complex adaptive components, hardware, and data, motivated an NSF-sponsored community workshop on the subject of Software Engineering for Robotics, held in Detroit, Michigan in October 2023. The goal of the workshop was to bring together thought leaders across robotics and software engineering to coalesce a community, and identify key problems in the area of SE for robotics that that community should aim to solve over the next 5 years. This report serves to summarize the motivation, activities, and findings of that workshop, in particular by articulating the challenges unique to robot software, and identifying a vision for fruitful near-term research directions to tackle them.