A Study on the Challenges of Using Robotics Simulators for Testing

TL;DR

This paper investigates the practical challenges faced by robotics developers in adopting simulation tools for testing, highlighting key barriers and suggesting directions for improving simulation technology.

Contribution

It provides a comprehensive survey of developers' experiences, identifying ten major challenges hindering simulation adoption in robotics testing.

Findings

85% of developers use simulation for testing

Major challenges include reality gap and resource costs

Guidelines for improving simulator development

Abstract

Robotics simulation plays an important role in the design, development, and verification and validation of robotic systems. Recent studies have shown that simulation may be used as a cheaper, safer, and more reliable alternative to manual, and widely used, process of field testing. This is particularly important in the context of continuous integration pipelines, where integrated automated testing is key to reducing costs while maintaining system safety. However, simulation and automated testing are not seeing the degree of widespread adoption in practice that their potential would motivate. Our goal in this paper is to develop a principled understanding of the ways developers use simulation in their process, and the challenges they face in doing so. This type of understanding can guide the development of more effective simulators and testing techniques for modern robotics development. To that end, we conduct a survey of 82 robotics developers from a diversity of backgrounds that addresses the current capabilities and limits of simulation technology in practice. We find that simulation is used by 85% of our participants for testing, and that many participants desire to use simulation as part of their test automation. We identify 10 high-level challenges that impede developers from using simulation for manual and automated testing, and general purposes. These challenges include the gap between simulation and reality, a lack of reproducibility, and considerable resource costs associated with using simulators. Finally, we outline avenues for improvement in the development of new simulators that can help simulation reach its potential as a means of verification and validation.