Robots are becoming more and more commonplace in many industry settings. This successful adoption can be partly attributed to (1) their increasingly affordable cost and (2) the possibility of developing intelligent, software-driven robots. Unfortunately, robotics software consumes significant amounts of energy. Moreover, robots are often battery-driven, meaning that even a small energy improvement can help reduce its energy footprint and increase its autonomy and user experience. In this paper, we study the Robot Operating System (ROS) ecosystem, the de-facto standard for developing and prototyping robotics software. We analyze 527 energy-related data points (including commits, pull-requests, and issues on ROS-related repositories, ROS-related questions on StackOverflow, ROS Discourse, ROS Answers, and the official ROS Wiki). Our results include a quantification of the interest of roboticists on software energy efficiency, 10 recurrent causes, and 14 solutions of energy-related issues, and their implied trade-offs with respect to other quality attributes. Those contributions support roboticists and researchers towards having energy-efficient software in future robotics projects.
Industry Best Practices in Robotics Software Engineering
Jet Propulsion Laboratory, California Institute of Technology（喷气推进实验室，加州理工学院）；Robert Bosch Corporate Research（罗伯特·博世企业研究院）；Waymo；XITASO GmbH（XITASO有限公司）；Mälardalen University（梅拉达伦大学）；Vrije Universiteit Amsterdam（阿姆斯特丹自由大学）；University of Stuttgart（斯图加特大学）
Mining beyond Earth with Space Robots: Exploration, Sampling, and Extraction
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；OpenSpace Lab（OpenSpace实验室）；School of Computation, Information and Technology, Technical University of Munich（慕尼黑工业大学计算、信息与技术学院）；University Research and Innovation Center, Obuda University（欧布达大学大学研究与创新中心）；School of Mechanical Engineering and Automation, Beihang University（北京航空航天大学机械工程及自动化学院）；School of Earth and Space Sciences, Wuhan University（武汉大学地球与空间科学学院）；Faculty of Mathematics and Computer Science, University of Würzburg（维尔茨堡大学数学与计算机科学学院）；School of Architecture & Urban Planning, Shenzhen University（深圳大学建筑与城市规划学院）；School of Mechanical and Electrical Engineering, China University of Mining and（中国矿业大学机电工程学院）
Ruhr University Bochum（鲁尔大学波鸿分校）；University of Bergamo（贝加莫大学）；Chalmers University of Technology（查尔姆斯理工大学）；University of Gothenburg（哥德堡大学）；Radboud University Nijmegen（奈梅亨拉德堡德大学）；Gran Sasso Science Institute (GSSI)（格兰萨索科学研究所）；Bergen University（卑尔根大学）
软件的质量通常被理解为“按照设计目的执行”，而安全性则意味着“软件不会使数据或计算系统面临未经授权访问的风险。“这两个方面之间似乎有联系，但是，我们如何将它们整合到机器人开发周期中？在本文中，我们将介绍DevSecOps in Robotics，这是一套最佳实践，旨在帮助机器人专家将安全性深入其开发和运营流程的核心。首先，我们简要介绍DevOps，介绍DevSecOps的附加值，并描述和说明如何在机器人领域实现这些实践。最后，我们讨论了安全，质量和安全，开放的问题和未来的研究问题之间的关系。
ROS-related Robotic Systems Development with V-model-based Application of MeROS Metamodel
Warsaw University of Technology, Institute of Control（华沙技术大学控制学院）；Warsaw University of Technology, Institute of Computer Science（华沙技术大学计算机科学学院）；Industrial Research Institute for Automation（自动化与测量工业研究院）；Ukrainian Catholic University, Applied Science Faculty（乌克兰天主教大学应用科学学院）
Australian Institute for Machine Learning（澳大利亚机器学习研究所）；Andy Thomas Centre for Space Resources（安迪·托马斯空间资源中心）；The University of Adelaide（阿德莱德大学）；SmartSat CRC（智能卫星合作研究中心）
