Vision devices are currently one of the most widely used sensory elements in robots: commercial autonomous cars and vacuum cleaners, for example, have cameras. These vision devices can provide a great amount of information about robot surroundings. However, platforms for robotics education usually lack such devices, mainly because of the computing limitations of low cost processors. New educational platforms using Raspberry Pi are able to overcome this limitation while keeping costs low, but extracting information from the raw images is complex for children. This paper presents an open source vision system that simplifies the use of cameras in robotics education. It includes functions for the visual detection of complex objects and a visual memory that computes obstacle distances beyond the small field of view of regular cameras. The system was experimentally validated using the PiCam camera mounted on a pan unit on a Raspberry Pi-based robot. The performance and accuracy of the proposed vision system was studied and then used to solve two visual educational exercises: safe visual navigation with obstacle avoidance and person-following behavior.

Open Vision System for Low-Cost Robotics Education

Lately, Kubernetes has begun to become an essential and ubiquitous component of cloud infrastructure This is due to the benefits that Kubernetes brings on the market, such as an application-focused interface, plug-and-play processes of horizontal scaling and self-healing mechanisms In this paper, we present the design and implementation of a model-based self-scaling solution for the RabbitMQ Kubernetes Cluster We first develop the Ansible formulas for the automatic provision of the infrastructure of the entire cluster Then, we use these models to dynamically determine the resources needed to complete RabbitMQ work, and we automatically perform a horizontal bridge self-scaling to successfully complete these jobs Our experimental results are on a single RabbitMQ Kubernetes cluster that is ready to be introduced in the IoT project

Autoscaled RabbitMQ Kubernetes Cluster on single-board computers

Yocto is a customizable lightweight Linux distribution for embedded devices with any kind of hardware architecture. With the Yocto, it is possible to compile an operating system with the same feature for the different types of hardware in a very short period of time. This paper proposed to use the Yocto with the Raspberry Pi to form a high-speed Internet of Things (IoT) hardware cum software solution with the only specific features that we need. The very common Linux distribution for the Raspberry Pi has a number of extra features that are not necessary for some dedicated applications like IoT application, which needs to run only some specific set of tasks. Here in this project, we designed a prototype of a smart home equipment control system with the two different models of Raspberry Pi and this embedded Linux operating system called Yocto. This system is able to control all the home equipment from the control interface display or from the specific website world wise.

Smart Home Equipment Control System with Raspberry Pi and Yocto

An increasing number of schools are teaching programming to their pupils and there is also an increase in programming in Higher Education with recent reports recommending this approach. At Manchester Metropolitan University (MMU) we wanted to attract and retain mathematics students and prepare them for careers upon graduation. By integrating Mathematics/Statistics/Operational Research packages across the curriculum and by solving real world problems we have managed to make the course highly desirable and loved by our students. In this case study, we show how it is possible to integrate programming and mathematical/computational modelling across the curriculum.

/pdf/programming-in-the-mathematics-curriculum-at-manchester-52w06n3q4k.pdf

Programming in the Mathematics Curriculum at Manchester Metropolitan University

The subjects of programming and robotics are quintessential subjects in today&#x2019;s world. The use of development boards like the Raspberry Pi and Arduino are making huge inroads into schools where they are used to teach the aforementioned subjects. But as the study explored, better interfaces can be built to simplify its ease of use and that is the motivation that has led to the development of the &#x2018;SPArK-Bot&#x2019; - an all-batteries-included educational robot that has the versatility of the Raspberry Pi with the simplicity of the Arduino all combined in a package that incentivizes the students to practice programming in a hands-on manner. Using standard hardware, but presenting them in a simple, fault tolerant way with tutorials to guide the students every step of the way resulted in a positive reaction from our evaluators with it scoring a perfect &#x2018;A Grade&#x2019; on the System Usability Scale (SUS). These evaluators include school students who are new to programming and college students who are well versed with the basics of programming. The college going students find that they can test out their ideas and easily prototype their proof of concept solutions and even use it in competitions. This system can be incorporated into existing curriculum and holistically help raise the bar for practical exposure and learning in this domain. 

SPArK-Bot: An Educational Robotic Platform

This paper describes the ideas of using Raspberry Pi computers in high schools and higher education Raspberry Pi is a powerful computer in a size of a credit card It was created by the Raspberry Pi Foundation charity, whose primary goal was the re-introduction of computer skills learning among students The Raspbian operating system is based on Linux and offers an excellent working environment for students, as it includes software solutions designed to expand students’ knowledge of computer science in an interesting way Besides computer science knowledge, it is also suitable for acquiring basic knowledge in electronics It is also very important to have the possibility of interconnecting such acquired knowledge Our students have adopted the knowledge how to install and use the Raspbian operating system, how to network and connect to the Internet, how to write programs using the Python programming language, and how to develop hardware-based projects From our own experience in Raspberry Pi we can conclude that this is an ideal platform for students to acquire new knowledge and competences in the field of computer science and electronics

Using Raspberry Pi Computers in Education

This paper describes the implementation of Arduino microprocessor platform in High school and College education. Here are presented preliminary experiences using the Arduino platform in the undergraduate computing curricula, at both the high school and college levels. The goal is to enhance student learning by engaging them in a project-based learning experience and introducing them to fundamental computing and engineering concepts in the context of a highly visual and easy to use environment. Given the really small cost of the Arduino and all of its available variants, it is a perfect platform. What we're finding is that when students are engaging more of their senses during the act of learning, they're more likely to integrate the concepts, since the Arduino really connects the physical world to the digital world.

Arduino Platform as Learning Tool in High School and College Education

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Using Raspberry Pi Computers in Education

Arduino Platform as Learning Tool in High School and College Education