Variability Modeling of Service Robots: Experiences and Challenges

Sergio García, D. Strüber, D. Brugali, Alessandro Di Fava, Philipp Schillinger, Patrizio Pelliccione, T. Berger
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引用次数: 31

Abstract

Sensing, planning, controlling, and reasoning, are human-like capabilities that can be artificially replicated in an autonomous robot. Such a robot implements data structures and algorithms devised on a large spectrum of theories, from probability theory, mechanics, and control theory to ethology, economy, and cognitive sciences. Software plays a key role in the development of robotic systems, as it is the medium to embody intelligence in the machine. During the last years, however, software development is increasingly becoming the bottleneck of robotic systems engineering due to three factors: (a) the software development is mostly based on community efforts and it is not coordinated by key stakeholders; (b) robotic technologies are characterized by a high variability that makes reuse of software a challenging practice; and (c) robotics developers are usually not specifically trained in software engineering. In this paper, we illustrate our experiences from EU, academic, and industrial projects in identifying, modeling, and managing variability in the domain of service robots. We hope to raise awareness for the specific variability challenges in robotics software engineering and to inspire other researchers to advance this field.
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服务机器人的可变性建模:经验与挑战
感知、规划、控制和推理都是类似人类的能力,可以在自主机器人中人工复制。这样的机器人实现了基于大量理论的数据结构和算法,从概率论、力学、控制理论到行为学、经济学和认知科学。软件在机器人系统的发展中起着关键作用,因为它是体现机器智能的媒介。然而,在过去的几年中,由于三个因素,软件开发日益成为机器人系统工程的瓶颈:(a)软件开发主要基于社区的努力,而不是由关键利益相关者协调;(b)机器人技术的特点是高度可变性,使得软件的重用成为一项具有挑战性的实践;(三)机器人开发人员通常没有受过软件工程方面的专门培训。在本文中,我们阐述了我们在服务机器人领域识别、建模和管理可变性方面的经验,这些经验来自欧盟、学术和工业项目。我们希望提高对机器人软件工程中特定变异性挑战的认识,并激励其他研究人员推进这一领域。
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