Study of Communication Issues in Dynamically Scalable Cloud-Based Vision Systems for Mobile Robots

Abstract

Thanks to the advent of technologies like Cloud Computing, the idea of computation offloading of robotic tasks is more than feasible. Therefore, it is possible to use legacy embedded systems for computationally heavy tasks like navigation or artificial vision, hence extending its lifespan. In this chapter we apply Cloud Computing for building a Cloud-Based 3D Point Cloud extractor for stereo images. The objective is to have a dynamically scalable solution (one of Cloud Computing's most important features) and applicable to near real-time scenarios. This last feature brings several challenges that must be addressed: meeting of deadlines, stability, limitation of communication technologies. All those elements will be thoroughly analyzed in this chapter, providing experimental results that prove the efficacy of the solution. At the end of the chapter, a successful use case of the platform is explained: navigation assistance.