Abstract

Cloud computing revealed recently to be of great interest in robotics. Indeed, it provides on-demand and elastic computing resources, database storage, and applications over the internet. These are major assets to improve robots' computational and cognitive capabilities, and share knowledge among the international robotic community. In this context, web services technologies are considered as a key factor for providing encapsulated and interoperable robotic services. However, finding the relevant robotic web service that can match the user request among the published services for different robots is still an issue. This paper presents a solution towards robotic web services discovery and selection in a cloud computing environment, based on Robot Operating System (ROS). We propose an approach, which aims to automate the robotic services search, and enables their use when needed ‘as a service’. This solution allows users to obtain the suitable service for their robots, according to a service-query matching score. To that end, we exploit the sentence-BERT model and reinforce the training dataset through ROS and robot tasks, which enhances significantly the performance of the discovery process. We conducted experiments over several ROS Web services using NAO robot. The obtained results are presented and discussed in this paper.

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