Building and evaluating cloud robotic systems: A systematic review

Abstract

Accelerated advancements in artificial intelligence and robotics have recently boosted the proliferation and adoption of robotic systems within various industries. In order to improve the capabilities of such systems that range from enabling remote processing to enhanced access to data, there has been integration of the cloud, and this gave rise to cloud robotics. Nevertheless, minimal published literature is available on a generic cloud robotic architecture that computer scientists or software developers can utilise and adapt to a particular use case scenario, as most existing cloud robotic architectures are scenario specific. To address this gap, a systematic review is conducted in this paper to illustrate the key components of cloud robotic systems through an architectural representation, in addition to enlighten how such systems are built and evaluated. For this, 44 recently published papers were systematically reviewed and analysed. Following the review, a generic architecture for cloud robotic system was realised, and it was found that there is no agreed consensus on the tools and technologies used in the build-up of such systems. Similarly, various approaches are used to evaluate such systems and the most common one is through case studies. However, there is a lack of frameworks that guide the evaluation process. This paper presents fascinating research concerns and potential for future study based on the data reported.