A Study on the Challenges of Using Robotics Simulators for Testing
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Abstract (arXiv)
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.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Apr 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 3; 2025: 4.
10 papers.
- 2023Scalable 3D Captioning with Pretrained Modelscited by 201
- 2025WorldGym: World Model as An Environment for Policy Evaluationcited by 61
- 2022Factory: Fast Contact for Robotic Assemblycited by 49
- 2025A Step Toward World Models: A Survey on Robotic Manipulationcited by 15
- 2024Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challengescited by 5
- 2021A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulationcited by 4
- 2025Sari Sandbox: A Virtual Retail Store Environment for Embodied AI Agentscited by 4
- 2025Learning to Evaluate Autonomous Behaviour in Human-Robot Interactioncited by 1
- 2024MORTAR: A Model-based Runtime Action Repair Framework for AI-enabled Cyber-Physical Systemscited by 0
- 2024QUB-PHEO: A Visual-Based Dyadic Multi-View Dataset for Intention Inference in Collaborative Assemblycited by 0
- 2025A Step Toward World Models: A Survey on Robotic Manipulation31 Oct 2025
- 2025Sari Sandbox: A Virtual Retail Store Environment for Embodied AI Agents1 Aug 2025
- 2025Learning to Evaluate Autonomous Behaviour in Human-Robot Interaction8 Jul 2025
- 2025WorldGym: World Model as An Environment for Policy Evaluation31 May 2025
- 2024QUB-PHEO: A Visual-Based Dyadic Multi-View Dataset for Intention Inference in Collaborative Assembly23 Sep 2024
- 2024MORTAR: A Model-based Runtime Action Repair Framework for AI-enabled Cyber-Physical Systems7 Aug 2024
- 2024Understanding How Blind Users Handle Object Recognition Errors: Strategies and Challenges6 Aug 2024
- 2023Scalable 3D Captioning with Pretrained Models12 Jun 2023
- 2022Factory: Fast Contact for Robotic Assembly7 May 2022
- 2021A Step Towards Efficient Evaluation of Complex Perception Tasks in Simulation28 Sep 2021