Robotic

In this study, Bug1, Bug2, Class1, Alg1, Alg2 and DistBug motion planning algorithms for mobile robots are simulated and their performances are compared.  These motion planning algorithms are applied on a Pioneer mobile robot on the simulation environment of MobileSim.  Sonar range sensors are used as the sensing element. This study shows that mobile robots build a new motion planning using the Bug’s algorithms only if they meet an unknown obstacle during their motion to goal. Each of the Bug’s algorithms is tested separately for two identical indoor environments. At the end of this study, the performance comparison of the Bug’s algorithms is shown.

Paper videos can be reached from this URL: http://www.youtube.com/playlist?list=PLENSkat0854sc3ir3uGysZefYqtdOxyr8

As the aging population and workforce constitute a worldwide concern, it is becoming necessary to predict how the dual threat of aging and technology at work increases the job vulnerability of older workers and jeopardizes their employability and permanence in the labor market. The objective of this paper is twofold: (1) to analyze perceptions of artificial intelligence, robotics, and automation in work settings and the expected impact of these technologies on older workers to contextualize this emergent phenomenon; and (2) to propose a general model related to "Agingand-Tech Job Vulnerability" to explain and predict the combined effect of aging and AI/robotics/ automation on job insecurity and additional outcomes among older workers. The propositions of the Age-and-Tech Job Vulnerability model developed in this paper seek to present a first approach for the conceptual advance and research on this emerging phenomenon and entails several theoretical and practical implications for organizational psychology.

This paper describes the MATLAB/SIMULINK realization of the PUMA 560 robot manipulator
position control methodology. This paper focuses on design, analyzed and implements nonlinear
computed torque control (CTC) methods. These simulation models are developed as a part of a
software laboratory to support and enhance graduate/undergraduate robotics courses, nonlinear
control courses and MATLAB/SIMULINK courses at research and development company (SSP
Co.) research center, Shiraz, Iran.

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of artificial intelligence (AI). In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a 'good AI society'. To do so, we examine how each report addresses the following three topics: (a) the development of a 'good AI society'; (b) the role and responsibility of the government, the private sector, and the research community (including academia) in pursuing such a development; and (c) where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a 'good AI society'. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach.

In October 2016, the White House, the European Parliament, and the UK House of Commons each issued a report outlining their visions on how to prepare society for the widespread use of AI. In this article, we provide a comparative assessment of these three reports in order to facilitate the design of policies favourable to the development of a 'good AI society'. To do so, we examine how each report addresses the following three topics: (a) the development of a 'good AI society'; (b) the role and responsibility of the government, the private sector, and the research community (including academia) in pursuing such a development; and (c) where the recommendations to support such a development may be in need of improvement. Our analysis concludes that the reports address adequately various ethical, social, and economic topics, but come short of providing an overarching political vision and long-term strategy for the development of a 'good AI society'. In order to contribute to fill this gap, in the conclusion we suggest a two-pronged approach.

Purpose – Extant research mainly focused on potentially negative customer responses to service robots. In contrast, our study is one of the first to explore a service context where service robots are likely to be the preferred service delivery mechanism over human frontline employees. Specifically, we examine how customers respond to service robots in the context of embarrassing service encounters.
>>> Design/methodology/approach – This study employs a mixed-method approach whereby an in-depth qualitative study (Study 1) is followed by two lab experiments (Studies 2 and 3).
>>> Findings – Results show that interactions with service robots attenuated customers’ anticipated embarrassment. Study 1 identifies a number of factors that can reduce embarrassment. These include the perception that service robots have reduced agency (e.g., are not able to make moral or social judgements) and emotions (e.g., are not able to have feelings). Study 2 tests our base model and shows that people feel less embarrassed during a potentially embarrassing encounter when interacting with service robots compared to frontline employees. Finally, Study 3 confirms that perceived agency, but not emotion, fully mediates frontline counterparty (employee vs. robot) effects on anticipated embarrassment.
>>> Practical implications – Service robots can add value by reducing potential customer embarrassment because they are perceived to have less agency than service employees. This makes service robots the preferred service delivery mechanism for at least some customers in potentially embarrassing service encounters (e.g., in certain medical contexts).
>>> Originality/value – This study is one of the first to examine a context where service robots are the preferred service delivery mechanism over human employees.

In this paper, a PD-serial fuzzy based robust nonlinear estimator for a robot manipulator is proposed by using robust factorization approach. That is, considering the uncertainties of dynamic model consisting of measurement error and disturbances, a PD with fuzzy estimator variable structure nonlinear feedback control scheme is designed to reduce effect of uncertainties. This research aims to design a new methodology to fix the position in robot manipulator. PD method is a linear methodology which can be used for highly nonlinear system’s (e.g., robot manipulator). To estimate this method, new serial fuzzy variable structure method (PD.FVSM) is used. This estimator can estimate the parameters to have the best performance.