Summary of Cloud Robot Research

Liu, Yi; Xu, Yuchun

doi:10.23919/iconac.2019.8895254

Cited by 10 publications

(5 citation statements)

References 9 publications

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“…AlphaGo [19] employed deep reinforcement learning strategies for designing the gameplay of Go). Further, simulation plays a major role in robotics, where systems like Amazon RoboMaker [23] and Unity Robotics simulation [24] provide a framework for the design and development of robotic systems through modeling and simulation.…”

Section: Methodsmentioning

confidence: 99%

AI-driven laboratory workflows enable operation in the age of social distancing

Marescotti

Narayanamoorthy²,

Bonjour

et al. 2022

SLAS Technology

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Section: Methodsmentioning

confidence: 99%

AI-driven laboratory workflows enable operation in the age of social distancing

Marescotti

Narayanamoorthy²,

Bonjour

et al. 2022

SLAS Technology

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“…Amazon is patronizing the AWS RoboMaker that provides machine learning, monitoring and analytics support to the robots. Microsoft has developed Robot Operating System (ROS) to program the robots with higher capacity [106]. Additionally, the Honda RaaS platform aims at providing a wide range of robot and cloud-based services to support communication, robotic cooperation, and data sharing.…”

Section: B Recent Industrial Practices Of Multi-agent Cloud Roboticsmentioning

confidence: 99%

Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey

Afrin

Jin

Rahman

et al. 2021

IEEE Commun. Surv. Tutorials

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Robotic applications nowadays are widely adopted to enhance operational automation and performance of real-world Cyber-Physical Systems (CPSs) including Industry 4.0, agriculture, healthcare, and disaster management. These applications are composed of latency-sensitive, data-heavy, and compute-intensive tasks. The robots, however, are constrained in the computational power and storage capacity. The concept of multi-agent cloud robotics enables robotto-robot cooperation and creates a complementary environment for the robots in executing large-scale applications with the capability to utilize the edge and cloud resources. However, in such a collaborative environment, the optimal resource allocation for robotic tasks is challenging to achieve. Heterogeneous energy consumption rates and application of execution costs associated with the robots and computing instances make it even more complex. In addition, the data transmission delay between local robots, edge nodes, and cloud data centres adversely affects the real-time interactions and impedes service performance guarantee. Taking all these issues into account, this paper comprehensively surveys the state-of-the-art on resource allocation and service provisioning in multi-agent cloud robotics. The paper presents the application domains of multi-agent cloud robotics through explicit comparison with the contemporary computing paradigms and identifies the specific research challenges. A complete taxonomy on resource allocation is presented for the first time, together with the discussion of resource pooling, computation offloading, and task scheduling for efficient service provisioning. Furthermore, we highlight the research gaps from the learned lessons, and present future directions deemed beneficial to further advance this emerging field.

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“…Another relevant example is cloud computing. For instance, Amazon RoboMaker (https://aws.amazon.com/robomaker/) [33] allows cloud robotics, simulating, and deploying robotic applications at a cloud-scale, which may then be available for distance students. It provides an integrated development environment, simulation service, and fleet management capabilities.…”

Section: Distance Learning In Roboticsmentioning

confidence: 99%

Open-Source Drone Programming Course for Distance Engineering Education

Plaza

Martín-Martín

Arias³

et al. 2020

Electronics

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This article presents a full course for autonomous aerial robotics inside the RoboticsAcademy framework. This “drone programming” course is open-access and ready-to-use for any teacher/student to teach/learn drone programming with it for free. The students may program diverse drones on their computers without a physical presence in this course. Unmanned aerial vehicles (UAV) applications are essentially practical, as their intelligence resides in the software part. Therefore, the proposed course emphasizes drone programming through practical learning. It comprises a collection of exercises resembling drone applications in real life, such as following a road, visual landing, and people search and rescue, including their corresponding background theory. The course has been successfully taught for five years to students from several university engineering degrees. Some exercises from the course have also been validated in three aerial robotics competitions, including an international one. RoboticsAcademy is also briefly presented in the paper. It is an open framework for distance robotics learning in engineering degrees. It has been designed as a practical complement to the typical online videos of massive open online courses (MOOCs). Its educational contents are built upon robot operating system (ROS) middleware (de facto standard in robot programming), the powerful 3D Gazebo simulator, and the widely used Python programming language. Additionally, RoboticsAcademy is a suitable tool for gamified learning and online robotics competitions, as it includes several competitive exercises and automatic assessment tools.

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Summary of Cloud Robot Research

Cited by 10 publications

References 9 publications

AI-driven laboratory workflows enable operation in the age of social distancing

AI-driven laboratory workflows enable operation in the age of social distancing

Resource Allocation and Service Provisioning in Multi-Agent Cloud Robotics: A Comprehensive Survey

Open-Source Drone Programming Course for Distance Engineering Education

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