A Review of exoskeleton-type systems and their key technologies

2008 ◽  
Vol 222 (8) ◽  
pp. 1599-1612 ◽  
Author(s):  
C-J Yang ◽  
J-F Zhang ◽  
Y Chen ◽  
Y-M Dong ◽  
Y Zhang
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Type System ◽  
Safety Evaluation ◽  
Type Systems ◽  
Machine Intelligence ◽  
System Structure ◽  
Design System ◽  
Key Technologies ◽  
High Level

The exoskeleton-type system is a brand new type of man—machine intelligent system. It fully combines human intelligence and machine power so that machine intelligence and human operator's power are both enhanced. Therefore, it achieves a high-level performance that neither could separately. This paper describes the basic exoskeleton concepts from biological system to man—machine intelligent systems. It is followed by an overview of the development history of exoskeleton-type systems and their two main applications in teleoperation and human power augmentation. Besides the key technologies in exoskeleton-type systems, the research is presented from several viewpoints of the biomechanical design, system structure modelling, cooperation and function allocation, control strategy, and safety evaluation.

scholarly journals Integrated AI Systems

AI Magazine ◽  
2020 ◽  
Vol 41 (2) ◽  
pp. 66-82
Author(s):  
Ronald Brachman ◽  
David Gunning ◽  
Murray Burke
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Decision Aids ◽  
Image Understanding ◽  
Machine Intelligence ◽  
Knowledge Representation And Reasoning ◽  
Personal Assistants ◽  
The 1960S ◽  
The Individual ◽  
Self Driving Cars

From Shakey the Robot to self-driving cars, from the personal computer to personal assistants on our phones, the Defense Advanced Research Projects Agency (DARPA) has led the development of integrated artificial intelligence (AI) systems for more than half a century. From the earliest days of AI, it was apparent that a robust, generally intelligent system should include a complete set of capabilities: perception, memory, reasoning, learning, planning, and action; and when DARPA initiated AI research in the 1960s, ambitious projects such as Shakey the Robot went after the complete package. As DARPA realized the challenges, they backed away from the ultimate goal of integrated AI and tried to make progress on the individual problems of image understanding, speech and language understanding, knowledge representation and reasoning, planning and decision aids, machine learning, and robotic manipulation. Yet, even as researchers struggled to make progress in these subdisciplines, DARPA periodically resurrected the challenge of integrated intelligent systems and pushed the community to try again. In the 1980s, DARPA’s Strategic Computing Initiative took on challenges of integrated AI projects such as the Autonomous Land Vehicle and the Pilot’s Associate. These did not succeed, but instead set the stage for the several decades of more siloed research that followed, until it was time to try again. In the 2000s, DARPA took on the integrated AI problem again with its Grand Challenges, which led to the first self-driving cars, and projects such as the Personalized Assistant that Learns, which produced Apple’s Siri. These efforts created complex, richly-integrated systems that represented quantum leaps ahead in machine intelligence. The integration of sophisticated capabilities in a fundamental way is the key to general intelligence. This is the story of DARPA’s persistent long-term support for this essential premise of AI

scholarly journals A certified lightweight non-interference Java bytecode verifier

2013 ◽  
Vol 23 (5) ◽  
pp. 1032-1081 ◽  
Author(s):  
GILLES BARTHE ◽  
DAVID PICHARDIE ◽  
TAMARA REZK
Keyword(s):  
Programming Languages ◽  
Information Flow ◽  
Type System ◽  
Type Systems ◽  
Program Execution ◽  
Flow Type ◽  
Java Bytecode ◽  
First Sound ◽  
Coq Proof Assistant ◽  
High Level

Non-interference guarantees the absence of illicit information flow throughout program execution. It can be enforced by appropriate information flow type systems. Much of the previous work on type systems for non-interference has focused on calculi or high-level programming languages, and existing type systems for low-level languages typically omit objects, exceptions and method calls. We define an information flow type system for a sequential JVM-like language that includes all these programming features, and we prove, in the Coq proof assistant, that it guarantees non-interference. An additional benefit of the formalisation is that we have extracted from our proof a certified lightweight bytecode verifier for information flow. Our work provides, to the best of our knowledge, the first sound and certified information flow type system for such an expressive fragment of the JVM.

AN INTRODUCTION TO AN EGOCENTRIC CONCEPT OF MACHINE INTELLIGENCE

1999 ◽  
Vol 08 (03) ◽  
pp. 313-336 ◽  
Author(s):  
RUDOLPH PIENNAR ◽  
JOHAN J. KRUGER
Keyword(s):  
System Design ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Physical Nature ◽  
Machine Intelligence ◽  
Robot Arm ◽  
Fundamental Building Block ◽  
Robot Arm Control ◽  
And Behavior ◽  
Physiological Research

Intimate to the functioning and behavior of intelligent systems is the manner in which information is represented internally. The conventional approach to intelligent system design assumes a particular bias in the manner by which this information is represented. Typically, this is characterized by an "abstract" or "objective" design methodology which holds that intelligence is not a function of the physical nature of the system. Such an approach suffers from several shortcomings, most notably problems relating to scaling and complexity. Recent physiological research, however, has demonstrated that physical bodily form is a fundamental building block in the organization of mammalian cortical structures. Consequently, this article explores such a biologically motivated "subjective" or "egocentric" approach to system design, and demonstrates its utility in a simple robot arm control problem.

Artificial intelligence as a moving force of improvement and innovative development in education and pedagogic

2019 ◽  
pp. 21-30
Author(s):  
M. G. Koliada ◽  
T. I. Bugayova
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Interaction Analysis ◽  
Educational Data Mining ◽  
Main Task ◽  
Intellectual System ◽  
Will Force ◽  
To Come ◽  
Artificial Intelligence Systems

The article discusses the history of the development of the problem of using artificial intelligence systems in education and pedagogic. Two directions of its development are shown: “Computational Pedagogic” and “Educational Data Mining”, in which poorly studied aspects of the internal mechanisms of functioning of artificial intelligence systems in this field of activity are revealed. The main task is a problem of interface of a kernel of the system with blocks of pedagogical and thematic databases, as well as with the blocks of pedagogical diagnostics of a student and a teacher. The role of the pedagogical diagnosis as evident reflection of the complex influence of factors and reasons is shown. It provides the intelligent system with operative and reliable information on how various reasons intertwine in the interaction, which of them are dangerous at present, where recession of characteristics of efficiency is planned. All components of the teaching and educational system are subject to diagnosis; without it, it is impossible to own any pedagogical situation optimum. The means in obtaining information about students, as well as the “mechanisms” of work of intelligent systems based on innovative ideas of advanced pedagogical experience in diagnostics of the professionalism of a teacher, are considered. Ways of realization of skill of the teacher on the basis of the ideas developed by the American scientists are shown. Among them, the approaches of researchers D. Rajonz and U. Bronfenbrenner who put at the forefront the teacher’s attitude towards students, their views, intellectual and emotional characteristics are allocated. An assessment of the teacher’s work according to N. Flanders’s system, in the form of the so-called “The Interaction Analysis”, through the mechanism of fixing such elements as: the verbal behavior of the teacher, events at the lesson and their sequence is also proposed. A system for assessing the professionalism of a teacher according to B. O. Smith and M. O. Meux is examined — through the study of the logic of teaching, using logical operations at the lesson. Samples of forms of external communication of the intellectual system with the learning environment are given. It is indicated that the conclusion of the found productive solutions can have the most acceptable and comfortable form both for students and for the teacher in the form of three approaches. The first shows that artificial intelligence in this area can be represented in the form of robotized being in the shape of a person; the second indicates that it is enough to confine oneself only to specially organized input-output systems for targeted transmission of effective methodological recommendations and instructions to both students and teachers; the third demonstrates that life will force one to come up with completely new hybrid forms of interaction between both sides in the form of interactive educational environments, to some extent resembling the educational spaces of virtual reality.

The Central Role of Cognitive Computations in Human-Information Interaction

2018 ◽  
Author(s):  
Wai-Tat Fu ◽  
Jessie Chin ◽  
Q. Vera Liao
Keyword(s):  
Information Systems ◽  
Cognitive Science ◽  
Intelligent Systems ◽  
Intelligent System ◽  
Levels Of Abstraction ◽  
Intelligent Information Systems ◽  
Emergent Behaviour ◽  
Information Interaction ◽  
Intelligent Information

Cognitive science is a science of intelligent systems. This chapter proposes that cognitive science can provide useful perspectives for research on technology-mediated human-information interaction (HII) when HII is cast as emergent behaviour of a coupled intelligent system. It starts with a review of a few foundational concepts related to cognitive computations and how they can be applied to understand the nature of HII. It discusses several important properties of a coupled cognitive system and their implication to designs of information systems. Finally, it covers how levels of abstraction have been useful for cognitive science, and how these levels can inform design of intelligent information systems that are more compatible with human cognitive computations.

scholarly journals Theoretical, Measured, and Subjective Responsibility in Aided Decision Making

2021 ◽  
Vol 11 (1) ◽  
pp. 1-37
Author(s):  
Nir Douer ◽  
Joachim Meyer
Keyword(s):  
Intelligent Systems ◽  
Intelligent System ◽  
Classification Systems ◽  
Strongly Correlated ◽  
Human Capabilities ◽  
Legal Decisions ◽  
Subjective Perceptions ◽  
Causal Responsibility ◽  
Quantification Model ◽  
Human Responsibility

When humans interact with intelligent systems, their causal responsibility for outcomes becomes equivocal. We analyze the descriptive abilities of a newly developed responsibility quantification model (ResQu) to predict actual human responsibility and perceptions of responsibility in the interaction with intelligent systems. In two laboratory experiments, participants performed a classification task. They were aided by classification systems with different capabilities. We compared the predicted theoretical responsibility values to the actual measured responsibility participants took on and to their subjective rankings of responsibility. The model predictions were strongly correlated with both measured and subjective responsibility. Participants’ behavior with each system was influenced by the system and human capabilities, but also by the subjective perceptions of these capabilities and the perception of the participant's own contribution. A bias existed only when participants with poor classification capabilities relied less than optimally on a system that had superior classification capabilities and assumed higher-than-optimal responsibility. The study implies that when humans interact with advanced intelligent systems, with capabilities that greatly exceed their own, their comparative causal responsibility will be small, even if formally the human is assigned major roles. Simply putting a human into the loop does not ensure that the human will meaningfully contribute to the outcomes. The results demonstrate the descriptive value of the ResQu model to predict behavior and perceptions of responsibility by considering the characteristics of the human, the intelligent system, the environment, and some systematic behavioral biases. The ResQu model is a new quantitative method that can be used in system design and can guide policy and legal decisions regarding human responsibility in events involving intelligent systems.

A system of constructor classes: overloading and implicit higher-order polymorphism

1995 ◽  
Vol 5 (1) ◽  
pp. 1-35 ◽  
Author(s):  
Mark P. Jones
Keyword(s):  
Type System ◽  
Type Systems ◽  
Natural Generalization ◽  
Higher Order ◽  
Functional Language ◽  
Effective Algorithm ◽  
Prototype Implementation ◽  
Type Classes

AbstractThis paper describes a flexible type system that combines overloading and higher-order polymorphism in an implicitly typed language using a system of constructor classes—a natural generalization of type classes in Haskell. We present a range of examples to demonstrate the usefulness of such a system. In particular, we show how constructor classes can be used to support the use of monads in a functional language. The underlying type system permits higher-order polymorphism but retains many of the attractive features that have made Hindley/Milner type systems so popular. In particular, there is an effective algorithm that can be used to calculate principal types without the need for explicit type or kind annotations. A prototype implementation has been developed providing, amongst other things, the first concrete implementation of monad comprehensions known to us at the time of writing.

The hybrid intelligent systems design using grey systems theory

2015 ◽  
Vol 5 (2) ◽  
pp. 194-205 ◽  
Author(s):  
Scarlat Emil ◽  
Virginia Mărăcine
Keyword(s):  
Systems Theory ◽  
Intelligent Systems ◽  
Explicit Knowledge ◽  
Intelligent System ◽  
Grey System Theory ◽  
Knowledge Flows ◽  
Content Type ◽  
Hybrid Intelligent Systems ◽  
Advantages And Disadvantages ◽  
Grey Systems Theory

Purpose – The purpose of this paper is to discuss how tacit and explicit knowledge determine grey knowledge and how these are stimulated through interactions within networks, forming the grey hybrid intelligent systems (HISs). The feedback processes and mechanisms between internal and external knowledge determine the apparition of grey knowledge into an intelligent system (IS). The extension of ISs is determined by the ubiquity of the internet but, in our framework, the grey knowledge flows assure the viability and effectiveness of these systems. Design/methodology/approach – Some characteristics of the Hybrid Intelligent Knowledge Systems are put forward along with a series of models of hybrid computational intelligence architectures. More, relevant examples from the literature related to the hybrid systems architectures are presented, underlying their main advantages and disadvantages. Findings – Due to the lack of a common framework it remains often difficult to compare the various HISs conceptually and evaluate their performance comparatively. Different applications in different areas are needed for establishing the best combinations between models that are designed using grey, fuzzy, neural network, genetic, evolutionist and other methods. But all these systems are knowledge dependent, the main flow that is used in all parts of every kind of system being the knowledge. Grey knowledge is an important part of the real systems and the study of its proprieties using the methods and techniques of grey system theory remains an important direction of the researches. Originality/value – The paper discusses the differences among the three types of knowledge and how they and the grey systems theory can be used in different hybrid architectures.

Hydrodynamic Design System for Pumps Based on 3-D CAD, CFD, and Inverse Design Method

2002 ◽  
Vol 124 (2) ◽  
pp. 329-335 ◽  
Author(s):  
Akira Goto ◽  
Motohiko Nohmi ◽  
Takaki Sakurai ◽  
Yoshiyasu Sogawa
Keyword(s):  
Computer Aided Design ◽  
High Performance ◽  
Design Method ◽  
High Reliability ◽  
Secondary Flows ◽  
System Structure ◽  
Inverse Design ◽  
Design System ◽  
Centrifugal Impeller ◽  
Inverse Design Method

A computer-aided design system has been developed for hydraulic parts of pumps including impellers, bowl diffusers, volutes, and vaned return channels. The key technologies include three-dimensional (3-D) CAD modeling, automatic grid generation, CFD analysis, and a 3-D inverse design method. The design system is directly connected to a rapid prototyping production system and a flexible manufacturing system composed of a group of DNC machines. The use of this novel design system leads to a drastic reduction of the development time of pumps having high performance, high reliability, and innovative design concepts. The system structure and the design process of “Blade Design System” and “Channel Design System” are presented. Then the design examples are presented briefly based on the previous publications, which included a centrifugal impeller with suppressed secondary flows, a bowl diffuser with suppressed corner separation, a vaned return channel of a multistage pump, and a volute casing. The results of experimental validation, including flow fields measurements, were also presented and discussed briefly.

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