Computer-based system for training and selecting mobile robot operators – evolving software tools

A part of research on application of mobots (mobile robots) for watching real environment isthe computer-based system for training and selecting candidates for mobot operators. The gameplayed by the candidates is the main part of the system. The core of the game is touring simulator.Firstly, it was assumed that speed of simulation would be a crucial factor for the game. Hence, theinitial version of the game was written in C++ for LAN. However, the experiments showed thatpromptness of the reaction of the game to the actions of the players was not so important. It turnedout that wide and easy access to the game and its remote management (e.g. via Internet) arenecessary. The current version of the game uses Java technology. Rewriting the game from C++ toJava created typical problems connected with moving an application from LAN to Internet. It wasnot a trivial problem. The paper evaluates and compares both versions of the game and describesproblems with migration from C++ to Java

An Application of Expectation-Maximization for Model Verification

A description which summarizes entire and usually big set of data is called its model. The problem investigated in the paper consists in verification of models of data coming from a simulation experiment of selecting candidates for operators of mobile robot (more strictly building reliable predictive model of the data). The models are validated using train-and-test method and verified with the help of the EM (expectation-maximization) algorithm which was originally designed for solving clustering problems with missing data. Actually, the selecting is a clustering problem because the candidates are assigned to ‘chosen’, ‘accepted’ or ‘rejected’ subgroups. For such a case the missing data is the category (the subgroup) for which a candidate should be assigned on the basis of his activity measured during the simulation experiment. The paper explains the procedure of model verification. It also shows experimental results and draws conclusions

Prospects of Mobile Search

Search faces (at least) two major challenges. One is to improve efficiency of retrieving relevant content for all digital formats (images, audio, video, 3D shapes, etc). The second is making relevant information retrievable in a range of platforms, particularly in high diffusion ones as mobiles. The two challenges are interrelated but distinct. This report aims at assessing the potential of future Mobile Search. Two broad groups of search-based applications can be identified. The first one is the adaptation and emulation of web search processes and services to the mobile environment. The second one is services exploiting the unique features of the mobile devices and the mobile environments. Examples of these context-aware services include location-based services or interfacing to the internet of things (RFID networks). The report starts by providing an introduction to mobile search. It highlights differences and commonalities with search technologies on other platforms (Chapter 1). Chapter 2 is devoted to the supply side of mobile search markets. It describes mobile markets, presents key figures and gives an outline of main business models and players. Chapter 3 is dedicated to the demand side of the market. It studies users¿ acceptance and demand using the results on a case study in Sweden. Chapter 4 presents emerging trends in technology and markets that could shape mobile search. It is the author's view after discussing with many experts. One input to this discussion was the analysis of on forward-looking scenarios for mobile developed by the authors (Chapter 5). Experts were asked to evaluate these scenarios. Another input was a questionnaire to which 61 experts responded. Drivers, barriers and enablers for mobile search have been synthesised into SWOT analysis. The report concludes with some policy recommendations in view of the likely socio-economic implications of mobile search in Europe.JRC.DG.J.4-Information Societ

An evolutionary approach to optimising neural network predictors for passive sonar target tracking

Object tracking is important in autonomous robotics, military applications, financial time-series forecasting, and mobile systems. In order to correctly track through clutter, algorithms which predict the next value in a time series are essential. The competence of standard machine learning techniques to create bearing prediction estimates was examined. The results show that the classification based algorithms produce more accurate estimates than the state-of-the-art statistical models. Artificial Neural Networks (ANNs) and K-Nearest Neighbour were used, demonstrating that this technique is not specific to a single classifier. [Continues.

Human-Machine Interfaces for Service Robotics

L'abstract è presente nell'allegato / the abstract is in the attachmen

Intern experience at Tech Tran Corporation, Naperville, Illinois: an internship report

"Submitted to the College of Engineering of Texas A&M University in partial fulfillment of the requirement for the degree of Doctor of Engineering."Includes vita (leaf 326)Includes "Selected glossary of robotics terms" (leaves 265-269, or p. 163-167 of original text)Includes bibliographical references (leaves 255-256, or p. 153-154 of original text)Includes text of work previously published: Sanderson, Ronald J. Industrial robots: a summary and forecast for manufacturing managers / Ronald J. Sanderson, John A. Campbell, John D. Meyer. Naperville, Ill.:Tech Tran Corporation, c1982. In addition to bearing leaf numbers 95-269 of the Record of Study, the pagination of the original publication is printed (vii, 1-167)This report presents a survey of the author's internship experience with Tech Tran Corporation during the period September 3, 1981 through April 30, 1982. The eight month internship was spent as an engineering intern with a small consulting firm specializing in high technology state-of-the-art manufacturing technology management and assessment. The intent of this report is to demonstrate that this experience fulfills the requirements of the Doctor of Engineering internship. The primary objective of the internship was to develop technical expertise in the field of industrial automation. Secondary goals were to improve oral and written communication skills and project management techniques. The three projects presented in this report met these objectives and goals. The major project was to develop a state-of-the-art assessment of robotics. This assessment was developed by surveying hundreds of robots users, manufacturers and researchers, and undertaking a comprehensive literature search on U.S. and foreign robots. The information was distilled into a professional managerial level report on robotics. The second project was to develop technical summaries and assessments of completed projects of the Army Missile Command's Manufacturing Technology Program. This was performed by reviewing project reports and interviewing government and contractor engineers throughout the country. The third project was to be an Associate Editor for Manufacturing Technoogy Horizons digest. This is a bi-monthly digest featuring major developments in manufacturing techniques and equipment. Short concise summaries for manufacturing processes were researched and developed through written correspondence and phone interviews. The internship was an opportunity to use my engineering skills to learn about the robotics industry, and improve oral and written communication skills. Thus, objectives for the Doctor of Engineering degree were met and the internship requirement satisfied

Mining conflicts around the world: Common grounds from an Environmental Justice perspective

Abstract. This report aims at exploring contemporary mining conflicts in the context of the sustainable development and environmental justice movement. This is done based on 24 real case studies from 18 different countries which are described by local activists and scholars. While 17 of the reported cases focus on conflicts related to metal mining (e.g. gold, silver, copper, zinc, and lead), four address uranium mining and one refers to coal mining. As an example of a new frontier in the industry, a sand mining conflict from India is also reported. All of these cases are directly chosen and reported, either in factsheet or in-depth study format, by EJOs, as part of a knowledge sharing activity well-established in EJOLT between EJOs and the academic community. Although the cases covered here are all quite unique and diverse in terms of type of conflict and geographical setting, they all share a common frame of analysis. First, the project and type of conflict are characterized in a nutshell, with some basic factual background that describe the companies involved, and the communities and locations affected. The roots of the conflicts are explored next, as well as relevant socioeconomic, cultural, health, and ecological impacts and related community claims. Where relevant, means of resistance are also specified with their influence on the project and/or the outcome of the conflict. The report then offers a synthesis of the described mining cases, review their commonalities, link gained insights with research needs and discuss some policy recommendations that might follow from this analysis. Despite its limitations, compiling such a diverse set of mining conflicts that builds on EJO knowledge promotes mutual learning and collaboration among stakeholders, EJOs and academia, which is one of the key objectives of EJOLT