MQTT and ROC Based Hybrid Robot as a Service (RaaS) Platform

Robots are rapidly evolving from factory work-horses to robot-companions. The future of robots will be as companions in the workplace functioning as interactive salespeople. In order to support this transition, it is important to combine service-oriented architecture and robotics. Service-oriented architecture and cloud computing have become dominant computing paradigms, and adding an RaaS (Robot as a Service) unit as a part of this system will help the companies manage and develop robots more efficiently. The major components of RaaS will be the integration of RMS (Robot Management System) and ROC (Robot Operation Center). As more and more robots are increasing in the service industry, the inter-robot communication is very critical. This communication can be achieved by ROC and the robots can be monitored remotely or locally via RMS. The RaaS platform will comply with all the standards of SOA (Service Oriented Architecture) like the development platform and execution unit, thereby creating a flexible and more development-friendly process

A Tradeoff Analysis of a Cloud-Based Robot Navigation Assistant Using Stereo Image Processing

The use of Cloud Computing for computation offloading in the robotics area has become a field of interest today. The aim of this work is to demonstrate the viability of cloud offloading in a low level and intensive computing task: a vision-based navigation assistance of a service mobile robot. In order to do so, a prototype, running over a ROS-based mobile robot (Erratic by Videre Design LLC) is presented. The information extracted from on-board stereo cameras will be used by a private cloud platform consisting of five bare-metal nodes with AMD Phenom 965 4 CPU, with the cloud middleware Openstack Havana. The actual task is the shared control of the robot teleoperation, that is, the smooth filtering of the teleoperated commands with the detected obstacles to prevent collisions. All the possible offloading models for this case are presented and analyzed. Several performance results using different communication technologies and offloading models are explained as well. In addition to this, a real navigation case in a domestic circuit was done. The tests demonstrate that offloading computation to the Cloud improves the performance and navigation results with respect to the case where all processing is done by the robot.Ministerio de Economía y Competitividad TEC2012-37868-C04-02/0

MQTT and ROC Based Hybrid Robot as a Service (RaaS) Platform

Robots are rapidly evolving from factory work-horses to robot-companions. The future of robots will be as companions in the workplace functioning as interactive salespeople. In order to support this transition, it is important to combine service-oriented architecture and robotics. Service-oriented architecture and cloud computing have become dominant computing paradigms, and adding an RaaS (Robot as a Service) unit as a part of this system will help the companies manage and develop robots more efficiently. The major components of RaaS will be the integration of RMS (Robot Management System) and ROC (Robot Operation Center). As robots are increasing in the service industry, the inter-robot communication is very critical

Enhancing Edge robotics through the use of context information

Cloud robotics aims at endowing robot systems with powerful capabilities by leveraging the computing resources available in theCloud. To that end, the Cloud infrastructure consolidates servicesand information among the robots, enabling a degree of centralization which has the potential to improve operations. Despite beingvery promising, Cloud robotics presents two critical issues: (i) it isvery hard to control the network between the robots and the Cloud(e.g., long delays, high jitter), and (ii) local context information (e.g.,on the access network) is not available in the Cloud. This makeshard to achieve deterministic performance for robotics applications.Over the last few years, Edge computing has emerged as a trend toprovide services and computing capabilities directly in the accessnetwork. This is so because of the additional benefits enabled byEdge computing: (i) it is easier to control the network end-to-end,and (ii) local context information (e.g., about the wireless channel) can be made available for use by applications. The goal of this paperis to showcase, by means of real-life experimentation, the benefits ofresiding at the Edge for robotics applications, due to the possibilityof consuming context information locally available. In our experimentation, an application running in the Edge controls over a Wi-Filink the movement of a robot. Information related to the wirelesschannel is made available via a service at the Edge, which is thenconsumed by the application.Results show that a smoother drivingof the robot can be achieved when wireless quality information isconsidered as input of the movement control algorithm.This article has been partially supported by the EU H2020 5G-CORAL Project (grant no. 761586) and by the 5G-City project (grant no. TEC2016-76795-C6-3-R) funded by the Spanish Ministry of Economy and Competitiveness

CCRP: A Novel Clone-Based Cloud Robotic Platform for Multi-Robots

Recently, the cloud computing paradigm has evolved from various research fields. A new path of research, cloud robotics, has emerged which allows robots to inherit the enormous computing and storage capability of cloud. Advances in cloud computing technologies, networking, parallel computing and other evolving technologies, and the integration with multi-robot systems, make it possible to design systems with new capabilities. The main advantages of cloud robotics are in overcoming the limitations of on-board robot computing and storage capabilities and in improving energy efficiency. Nevertheless, there is a lack of cloud robotics frameworks that can provide a secured environment for multi-robot application. The implementation of a robust cloud robotic platform capable of handling multi-robot applications has been shown to be challenging. This research proposes a novel Clone-based Cloud Robotic Platform architecture (CCRP) which assigns a Virtual Machine (VM) clone of each individual robot's operating system in the cloud, enabling fast and efficient collaboration between them via the cloud's inner-network. The system utilises Robot Operating System (ROS) as a middleware and programmable environment for robot development. This model is using the OpenVPN as a communication protocol between the robot and the VM, which provides considerable enhancement for the security and additional network for the system to allow multi-master ROS deployment. The Quality of Service (QoS) for the system has been tested and evaluated in terms of performance, compatibility and scalability via comparison study, which examines the CCRP performance against a local system and a proxy-based cloud system. Two case studies have been deployed for different robot scenarios. Case study 1 was focused on a navigation task which includes the process of mapping and teleoperation implemented in Google public cloud. The real time response has been examined by using the CCRP to teleoperate the NAO and Turtlebot robots. A response time and video streaming delays were measured to assess the overall QoS performance. Case study 2 is composed of a face recognition task performed using the CCRP in a private cloud on an Openstack platform. The objective of this task was to evaluate the system ability of running the tasks in the cloud effectively and to assess the collaborative learning capability. During the CCRP development and deployment stages an optimization study was conducted to determine optimal parameters for data offloading to the cloud and energy efficiency of a low-cost robot. The result of the CCRP performance evaluation proved that it is capable of running on a public and private cloud platform for self-configuring and programmable robotic systems, as well as executing various applications on different robot types. The CCRP is facilitating the improvements to QoS performance, compatibility and scalability and is providing a secure cloud computing environment for on-board robots