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.
UAIbot: Beginner-friendly web-based simulator for interactive robotics learning and research
Graduate Program in Electrical Engineering - Universidade Federal de Minas Gerais - Av. Antônio Carlos 6627, 31270-901, Belo Horizonte, MG, Brazil(巴西米纳斯吉拉斯联邦大学电气工程研究生项目);Comenius University, Bratislava, Slovakia(斯洛伐克布拉迪斯拉发康门纽斯大学)
A Comparison of Humanoid Robot Simulators: A Quantitative Approach
Escola Politécnica de Pernambuco, Universidade de Pernambuco(伯南布哥大学伯南布哥理工学院);Escuela de Ingeniería, Universidad Central de Chile(智利中央大学工程学院);School of Information Technology, Deakin University(迪肯大学信息技术学院)
DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting
NVIDIA(英伟达);University of Southern California(南加州大学);University of Toronto(多伦多大学);Vector Institute(向量研究所);University of Washington(华盛顿大学);University of Sydney(悉尼大学)
DiSECt: A Differentiable Simulator for Parameter Inference and Control in Robotic Cutting
University of Southern California(南加州大学);NVIDIA(英伟达);University of Washington(华盛顿大学);University of Toronto(多伦多大学);Vector Institute(向量研究所);University of Sydney(悉尼大学)
RoboGSim: A Real2Sim2Real Robotic Gaussian Splatting Simulator
Harbin Institute of Technology, Shenzhen(哈尔滨工业大学(深圳));Institute of Computing Technology, Chinese Academy of Sciences(中国科学院计算技术研究所);MEGVII Technology(商汤科技);Zhejiang University(浙江大学)
Before Autonomy Takes Control: Software Testing in Robotics
Ruhr University Bochum Bochum Germany;University of Bremen Bremen Germany;IT University of Copenhagen Copenhagen Denmark;Chalmers\,|\,Gothenburg University Gothenburg Sweden;Ruhr University Bochum;University of Bremen;IT University of Copenhagen;Chalmers\,|\,Gothenburg University
Kilombo: a Kilobot simulator to enable effective research in swarm robotics
University of Amsterdam(阿姆斯特丹大学);John Innes Centre(约翰·英纳斯中心);Centre for Genomic Regulation (CRG)(基因组调控中心(CRG));The Barcelona Institute of Science and Technology(巴塞罗那科学技术学院);Universitat Pompeu Fabra (UPF)(庞培法布拉大学(UPF));Institució Catalana de Recerca i Estudis Avançats (ICREA)(加泰罗尼亚研究与高等教育机构(ICREA));Delft University of Technology(代尔夫特理工大学);Åbo Akademi University(奥博学术大学)
Closed loop interactions between spiking neural network and robotic simulators based on MUSIC and ROS
Institute for Advanced Simulation (IAS-6), Theoretical Neuroscience(高等模拟研究所(IAS-6),理论神经科学);Institute of Neuroscience and Medicine (INM-6), Computational and Systems Neuroscience(神经科学与医学研究所(INM-6),计算与系统神经科学);JARA BRAIN Institute I(JARA BRAIN 研究所 I);Jülich Research Center(于利希研究中心);JARA Jülich(JARA 于利希);PDC Center for High Performance Computing KTH Stockholm(KTH 斯德哥尔摩高性能计算中心);Faculty of Biology Albert-Ludwig University of Freiburg(弗赖堡阿尔伯特-路德维希大学生物学院);Bernstein Center Freiburg Albert-Ludwig University of Freiburg(弗赖堡阿尔伯特-路德维希大学伯恩斯坦中心)
Two is Better Than One: Digital Siblings to Improve Autonomous Driving Testing
Università della Svizzera italiana (USI)(瑞士意大利语区大学);Technical University of Munich(慕尼黑工业大学);fortiss GmbH(fortiss有限公司);Università degli Studi di Udine(乌迪内大学)
Runtime Verification and Field-based Testing for ROS-based Robotic Systems
Chalmers University of Technology(查尔姆斯理工大学);Gran Sasso Science Institute (GSSI)(格兰萨索科学研究所);University of Brasilia(巴西利亚大学);Ruhr University Bochum(波鸿鲁尔大学);University of Gothenburg(哥德堡大学)
It Takes Two to Tango: A Holistic Simulator for Joint Order Scheduling and Multi-Agent Path Finding in Robotic Warehouses
East China Normal University(东华大学);Tongji University(同济大学);Zhejiang Galaxis Technology Group Co.,Ltd(浙江伽利西科技集团有限公司);Shenzhen Loop Area Institute (SLAI)(深圳环 area 研究院)
Contact Models in Robotics: a Comparative Analysis
Inria(法国国家信息与自动化研究所);École normale supérieure(巴黎高等师范学院);PSL Research University(巴黎文理研究大学);LAAS-CNRS(法国国家科学研究中心自动化与系统分析实验室);Czech Institute of Informatics, Robotics and Cybernetics(捷克信息学、机器人学与控制论研究所);Czech Technical University(捷克技术大学)
A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI
Department of Computer Science, City University of Hong Kong(城市大学计算机科学系);School of Electrical and Electronic Engineering, Nanyang Technological University(南洋理工大学电子与电气工程学院);Department of Informatics, Universität Hamburg(汉堡大学信息学院)