NUST Institutions Library Catalogue Search for 'kw,wrdl: (su-br:"Robots.")'

Cambrian Intelligence : The Early History of the New AI /

By Brooks, Rodney A.. Cambridge : MIT Press 1999 0262024683 (Trade Cloth)

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Handbook of ambient intelligence and smart environments \

By Nakashima, Hideyuki.. New York : Springer, 2010 9780387938073 (hbk.)

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Robots, Reasoning, and Reification /

By Gunderson, James P.. 9781441946805

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Unmanned Aerial Vehicles /

By Valavanis, Kimon P.. 2011 9789400711099

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Mechanics of robotic manipulation /

By Mason, Matthew T.. Cambridge, Mass. : MIT Press, 2001 . xi, 253 p. : , "A Bradford book." 24 cm.. 0262133962 (hc. : alk. paper)

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Bio-Inspired Self-Organizing Robotic Systems /

By Meng, Yan.. 9783642207594

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Biologically Inspired Approaches for Locomotion, Anomaly Detection and Reconfiguration for Walking Robots

By Jakimovski, Bojan.. 9783642225055 | 9783642225048 (print)

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Modelling and Control for Intelligent Industrial Systems : Adaptive Algorithms in Robotics and Industrial Engineering /

By Rigatos, Gerasimos G.. 9783642178740

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Introduction to autonomous mobile robots /

By Siegwart, Roland.. Cambridge, Mass. : MIT Press, 2004 . ix, 321 p. : , "A Bradford book." 24 cm.. 026219502X (hc : alk. paper)

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Principles of robot motion : theory, algorithms, and implementation /

By Choset, Howie. Cambridge, Mass. : MIT Press, 2005 . xix, 603 p. : , "A Bradford book." 24 cm.. 0262033275 (alk. paper)

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Dune. The Battle of Corrin /

By Herbert, Brian.. New York : Tor, 2004 . 580 p. : , Sequel to: Dune. The machine crusade. | "A Tom Doherty Associates book." 25 cm.. 9780340823385

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Robotics, Vision and Control : Fundamental Algorithms In MATLAB® Second, Completely Revised, Extended And Updated Edition /

By Corke, Peter.. . 1 online resource (XXIX, 693 pages 402 illustrations, 335 illustrations in color.) 9783319544137

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Artificial Intelligence for Robotics/ Bring a new degree of interconnectivity to your world by building your own intelligent robots

By Govers, Francis X. Packt UK 2018 . v, 331: pages 978-1-78883-544-2

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Comparison of Quantitative Proxemics to measure trust in HRI /

By Ahmad, Fatima . . 45p. ; 30cm..

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Perception of Emotion in Human-Robot Interaction /

By Zia, Muhammad Faisal. . 59p. , Perception of emotion is an intuitive replication of a person’s internal state without the need for verbal communication. Visual emotion recognition has been broadly studied and several end-toend deep neural networks (DNNs)-based and Machine learning-based models have been proposed but they lack the ability to be implemented in low-specification devices like robots, and vehicles. The drawbacks of conventional handcrafted feature-based Facial Emotion Recognition (FER) methods are eliminated by DNNs-based FER approaches. In spite of that, Deep Neural Network based FER techniques suffer from high processing costs and exorbitant memory requirements, their application is constrained in fields like Human-Robot Interaction (HRI) and HumanComputer Interaction (HCI) and relies on hardware requirements. In aforementioned study, we presented a computationally inexpensive and robust FER system for the perception of six basic emotions (i.e., disgust, surprise, fear, anger, happy, and sad) that is capable of running on embedded devices with constrained specifications. In the first step after pre-processing input images, geometric features are extracted from detected facial landmarks, considering the facial spatial position among influential landmarks. The extracted features are given as input to trainthe SVM classifier. Our proposed FER system was trained and evaluated experimentally using two databases, Karolinska Directed Emotional Faces (KDEF) and Extended Cohn-Kanade (CK+) database. Fusion of KDEF and CK+ datasets at the training level were also employed in order to generalize the FER system’s response to the variations of ethnicity, race, national and provincial backgrounds. The results show that our proposed FER system is optimized for real-time embedded applications with constrained specifications and yields an accuracy of 96.8%, 86.7% and 86.4% for CK+, KDEF and fusion of CK+ and KDEF databases respectively. As a part of our future research objectives, the developed system will make a robotic agent capable of perceiving emotion and interacting naturally without the need for additional hardware during HRI. 30cm.

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Fixed-Value MBLL based Cognitive Hemodynamic response assessment using P-fNIRS system: Applications to Deep Learning Brain Machine Interface (BMI) /

By Asgher,Umer . . 172p. , Humans in the modern systems not only interact with other humans but also have to interact with intelligent machines, robots in form of cyber physical systems to collaborate in order to carry out different tasks in real working environment. The modern Industrial system comprises of humans, machines, and cyber systems with a collective aim of optimized industrial manufacturing objectives, human factors, and ergonomics goals. Different macrohuman factors are considered while designing and formulating human work safety of such systems and one of the important neuroergonomic factors in is the Cognitive and Mental Workload (C-MWL). The mental workload (MWL) in the human’s brain is measured with difference non-invasive neuroimaging techniques. Most of the cognitive load measuring methods either require massive system protocols like fMRI (functional magnetic resonance imagining), positron-emission tomography (PET) or strict human anatomical movements restrictions like electroencephalogram (EEG) and magnetoencephalography (MEG). To address these limitations, fNIRS (functional Near infrared Spectroscopy) is used in this research to measure the hemodynamic changes in the human brain’s tissues as a measure of the brain activity. The brain’s hemodynamic signals are measured using a light weight portable fNIRS system (P-fNIRSSyst) that is designed to measure relative change in concentration of chromophores (oxy and deoxy hemoglobin) in brain tissues. In this study a novel variant of MBLL (Modified Beer-lambert Law) is designed by keeping the previous intensity value as a reference by taking the average from initial four seconds activity stimuli in optical density. The four second stimuli average in novel and important in calculation the changes in concentration of chromophores. This novel variant of MBLL is Fixed Value - Modified Beer-lambert Law (FV-MBLL). In this research, MWL is measured and classified in different real time working environments. The two-state cognitive load is measured with fNIRS system and classified using FV-MBLL using machine learning techniques like k-nearest neighbors (k-NN), support vector machines (SVM), and artificial neural networks (ANN). The classification accuracies of FV-MBLL are better than MBLL. The research further explores the classification capabilities of deep neural networks (DNN) such as convolutional neural network s (CNN) and Long short-term memory (LSTM) for the first time in assessment and classification of four- iv state MWL. The classification accuracies of LSTM outperform not only ML algorithms (SVM, KNN and ANN) but CNN as well in classification of multi-state MWL. The research experimental validation is performed using the accuracies with MWL that are further utilized in neurorehabilitation as neurofeedback to operate bionic systems using Brain Machine Interface (BMI). 30cm.

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Multi-Robot Interactive Therapy for Children with Autism Spectrum Disorder /

By Ali ,Sara . . 139p. , Robot-Assisted Therapies (RAT) is an emerging field and has shown promising results. Recently, one of the prominent applications of robots is assistive therapy is for Autism Spectrum Disorder (ASD). Autism Spectrum Disorder is a set of neurodevelopment disorder affecting 7.5 million people around the world. Children with ASD lack social and communication skills which affects their ability in schools as well as in community. Recently, humanoid robots are used for the treatment of children with autism spectrum disorder to improve the development of communicational, behavioral, motor movements, joint attention, and physical behaviors. These interactive interventions that use robots for children with ASD, is one of the favorable tools for improving the behavior of children. In particular, the area of robotics is helping a lot in the treatment of ASD as the robot acts as a mediator as well as measures the response of an autistic child. However, the research aiming that the treatment of children with autism is limited, these therapies introduced by robots are successful in establishing basic communication skills. This research has proposed a novel mathematical model for an adaptive therapy of children with Autism Spectrum Disorder called Multi-robot-mediated Intervention System (MRIS). Three different therapies related to improvement in joint attention and imitation skills, effective human-human interaction and comparison of effective stimulus are introduced under this mathematical model. This research aims to introduce multi-sensory data that provides the quantitative support for improvement in social skills of children with autism, replacing the current techniques of measuring the improvement from physically observing the ASD child and with video analysis. Besides ensuring the accuracy in results, this method also introduces consistency as robots are immune to fatigue, unlike humans. The effectiveness of the model has been validated using cognitive brain state of the children with Electroencephalogram (EEG) neuroheadsets. Moreover, the effectiveness of the results has been validated using statistical analysis and the Childhood Autism Rating Scale (CARS). 30cm.

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