15,885 research outputs found
Integrating mobile robotics and vision with undergraduate computer science
This paper describes the integration of robotics education into an undergraduate Computer Science curriculum. The proposed approach delivers mobile robotics as well as covering the closely related field of Computer Vision, and is directly linked to the research conducted at the authorsâ institution. The paper describes the most relevant details of the module content and assessment strategy, paying particular attention to the practical sessions using Rovio mobile robots. The specific choices are discussed that were made with regard to the mobile platform, software libraries and lab environment. The paper also presents a detailed qualitative and quantitative analysis of student results, including the correlation between student engagement and performance, and discusses the outcomes of this experience
Unifying an Introduction to Artificial Intelligence Course through Machine Learning Laboratory Experiences
This paper presents work on a collaborative project funded by the National Science Foundation that incorporates machine learning as a unifying theme to teach fundamental concepts typically covered in the introductory Artificial Intelligence courses. The project involves the development of an adaptable framework for the presentation of core AI topics. This is accomplished through the development, implementation, and testing of a suite of adaptable, hands-on laboratory projects that can be closely integrated into the AI course. Through the design and implementation of learning systems that enhance commonly-deployed applications, our model acknowledges that intelligent systems are best taught through their application to challenging problems. The goals of the project are to (1) enhance the student learning experience in the AI course, (2) increase student interest and motivation to learn AI by providing a framework for the presentation of the major AI topics that emphasizes the strong connection between AI and computer science and engineering, and (3) highlight the bridge that machine learning provides between AI technology and modern software engineering
Enhancing Undergraduate AI Courses through Machine Learning Projects
It is generally recognized that an undergraduate introductory Artificial Intelligence course is challenging to teach. This is, in part, due to the diverse and seemingly disconnected core topics that are typically covered. The paper presents work funded by the National Science Foundation to address this problem and to enhance the student learning experience in the course. Our work involves the development of an adaptable framework for the presentation of core AI topics through a unifying theme of machine learning. A suite of hands-on semester-long projects are developed, each involving the design and implementation of a learning system that enhances a commonly-deployed application. The projects use machine learning as a unifying theme to tie together the core AI topics. In this paper, we will first provide an overview of our model and the projects being developed and will then present in some detail our experiences with one of the projects â Web User Profiling which we have used in our AI class
Using Scratch to Teach Undergraduate Students' Skills on Artificial Intelligence
This paper presents a educational workshop in Scratch that is proposed for
the active participation of undergraduate students in contexts of Artificial
Intelligence. The main objective of the activity is to demystify the complexity
of Artificial Intelligence and its algorithms. For this purpose, students must
realize simple exercises of clustering and two neural networks, in Scratch. The
detailed methodology to get that is presented in the article.Comment: 6 pages, 7 figures, workshop presentatio
Learning while Competing -- 3D Modeling & Design
The e-Yantra project at IIT Bombay conducts an online competition, e-Yantra
Robotics Competition (eYRC) which uses a Project Based Learning (PBL)
methodology to train students to implement a robotics project in a step-by-step
manner over a five-month period. Participation is absolutely free. The
competition provides all resources - robot, accessories, and a problem
statement - to a participating team. If selected for the finals, e-Yantra pays
for them to come to the finals at IIT Bombay. This makes the competition
accessible to resource-poor student teams. In this paper, we describe the
methodology used in the 6th edition of eYRC, eYRC-2017 where we experimented
with a Theme (projects abstracted into rulebooks) involving an advanced topic -
3D Designing and interfacing with sensors and actuators. We demonstrate that
the learning outcomes are consistent with our previous studies [1]. We infer
that even 3D designing to create a working model can be effectively learned in
a competition mode through PBL
Face of the Future
Paul Oh, robotics visionary, believes Nevada is poised to become the nationâs premier destination for all manner of âunmanned systems,â those technological marvels that are rapidly redrawing the boundaries between man and machine
Space education: Deriving benefits from industrial consortia
As the number of spacefaring nations of the world increases, so does the difficulty of competing in a global economy. The development of high technology products and services for space programs, and the economic exploitation of these technologies for national economic growth, requires professionals versed in both technical and commercial aspects of space. Meeting this requirement academically presents two challenges. On the technical side, enrollment in science and engineering is decreasing in some of the spacefaring nations. From the commerce perspective, very few colleges and universities offer specific courses in space business
Mobile Robot Lab Project to Introduce Engineering Students to Fault Diagnosis in Mechatronic Systems
This document is a self-archiving copy of the accepted version of the paper.
Please find the final published version in IEEEXplore: http://dx.doi.org/10.1109/TE.2014.2358551This paper proposes lab work for learning fault detection and diagnosis (FDD) in mechatronic systems. These skills are important for engineering education because FDD is a key capability of competitive processes and products. The intended outcome of the lab work is that students become aware of the importance of faulty conditions and learn to design FDD strategies for a real system. To this end, the paper proposes a lab project where students are requested to develop a discrete event dynamic system (DEDS) diagnosis to cope with two faulty conditions in an autonomous mobile robot task. A sample solution is discussed for LEGO Mindstorms NXT robots with LabVIEW. This innovative practice is relevant to higher education engineering courses related to mechatronics, robotics, or DEDS. Results are also given of the application of this strategy as part of a postgraduate course on fault-tolerant mechatronic systems.This work was supported in part by the Spanish CICYT under Project DPI2011-22443
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