3,017 research outputs found
Implications of the Google’s US 8,996,429 B1 Patent in Cloud Robotics-Based Therapeutic Researches
Intended for being informative to both legal and engineer communities, this chapter raises awareness on the implications of recent patents in the field of human-robot interaction (HRI) studies. Google patented the use of cloud robotics to create robot personality(-ies). The broad claims of the patent could hamper many HRI research projects in the field. One of the possible frustrated research lines is related to robotic therapies because the personalization of the robot accelerates the process of engagement, which is extremely beneficial for robotic cognitive therapies. This chapter presents, therefore, the scientific examination, description, and comparison of the Tufts University CEEO project “Data Analysis and Collection through Robotic Companions and LEGO® Engineering with Children on the Autism Spectrum project” and the US 8,996,429 B1 Patent on the Methods and Systems for Robot Personality Development of Google. Some remarks on ethical implications of the patent will close the chapter and open the discussion to both communities
Improving National and Homeland Security through a proposed Laboratory for Information Globalization and Harmonization Technologies (LIGHT)
A recent National Research Council study found that: "Although there are many private and public databases that
contain information potentially relevant to counter terrorism programs, they lack the necessary context definitions
(i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and
timely information" [NRC02, p.304, emphasis added] That sentence succinctly describes the objectives of this
project. Improved access and use of information are essential to better identify and anticipate threats, protect
against and respond to threats, and enhance national and homeland security (NHS), as well as other national
priority areas, such as Economic Prosperity and a Vibrant Civil Society (ECS) and Advances in Science and
Engineering (ASE). This project focuses on the creation and contributions of a Laboratory for Information
Globalization and Harmonization Technologies (LIGHT) with two interrelated goals:
(1) Theory and Technologies: To research, design, develop, test, and implement theory and technologies for
improving the reliability, quality, and responsiveness of automated mechanisms for reasoning and resolving semantic
differences that hinder the rapid and effective integration (int) of systems and data (dmc) across multiple
autonomous sources, and the use of that information by public and private agencies involved in national and
homeland security and the other national priority areas involving complex and interdependent social systems (soc).
This work builds on our research on the COntext INterchange (COIN) project, which focused on the integration
of diverse distributed heterogeneous information sources using ontologies, databases, context mediation algorithms,
and wrapper technologies to overcome information representational conflicts. The COIN approach makes it
substantially easier and more transparent for individual receivers (e.g., applications, users) to access and exploit
distributed sources. Receivers specify their desired context to reduce ambiguities in the interpretation of information
coming from heterogeneous sources. This approach significantly reduces the overhead involved in the integration of
multiple sources, improves data quality, increases the speed of integration, and simplifies maintenance in an
environment of changing source and receiver context - which will lead to an effective and novel distributed
information grid infrastructure. This research also builds on our Global System for Sustainable Development
(GSSD), an Internet platform for information generation, provision, and integration of multiple domains, regions,
languages, and epistemologies relevant to international relations and national security.
(2) National Priority Studies: To experiment with and test the developed theory and technologies on practical
problems of data integration in national priority areas. Particular focus will be on national and homeland security,
including data sources about conflict and war, modes of instability and threat, international and regional
demographic, economic, and military statistics, money flows, and contextualizing terrorism defense and response.
Although LIGHT will leverage the results of our successful prior research projects, this will be the first research
effort to simultaneously and effectively address ontological and temporal information conflicts as well as
dramatically enhance information quality. Addressing problems of national priorities in such rapidly changing
complex environments requires extraction of observations from disparate sources, using different interpretations, at
different points in times, for different purposes, with different biases, and for a wide range of different uses and
users. This research will focus on integrating information both over individual domains and across multiple domains.
Another innovation is the concept and implementation of Collaborative Domain Spaces (CDS), within which
applications in a common domain can share, analyze, modify, and develop information. Applications also can span
multiple domains via Linked CDSs. The PIs have considerable experience with these research areas and the
organization and management of such large scale international and diverse research projects.
The PIs come from three different Schools at MIT: Management, Engineering, and Humanities, Arts & Social
Sciences. The faculty and graduate students come from about a dozen nationalities and diverse ethnic, racial, and
religious backgrounds. The currently identified external collaborators come from over 20 different organizations
and many different countries, industrial as well as developing. Specific efforts are proposed to engage even more
women, underrepresented minorities, and persons with disabilities.
The anticipated results apply to any complex domain that relies on heterogeneous distributed data to address and
resolve compelling problems. This initiative is supported by international collaborators from (a) scientific and
research institutions, (b) business and industry, and (c) national and international agencies. Research products
include: a System for Harmonized Information Processing (SHIP), a software platform, and diverse applications in
research and education which are anticipated to significantly impact the way complex organizations, and society in
general, understand and manage critical challenges in NHS, ECS, and ASE
Improving National and Homeland Security through a proposed Laboratory for nformation Globalization and Harmonization Technologies (LIGHT)
A recent National Research Council study found that: "Although there are many private and public databases that
contain information potentially relevant to counter terrorism programs, they lack the necessary context definitions
(i.e., metadata) and access tools to enable interoperation with other databases and the extraction of meaningful and
timely information" [NRC02, p.304, emphasis added] That sentence succinctly describes the objectives of this
project. Improved access and use of information are essential to better identify and anticipate threats, protect
against and respond to threats, and enhance national and homeland security (NHS), as well as other national
priority areas, such as Economic Prosperity and a Vibrant Civil Society (ECS) and Advances in Science and
Engineering (ASE). This project focuses on the creation and contributions of a Laboratory for Information
Globalization and Harmonization Technologies (LIGHT) with two interrelated goals:
(1) Theory and Technologies: To research, design, develop, test, and implement theory and technologies for
improving the reliability, quality, and responsiveness of automated mechanisms for reasoning and resolving semantic
differences that hinder the rapid and effective integration (int) of systems and data (dmc) across multiple
autonomous sources, and the use of that information by public and private agencies involved in national and
homeland security and the other national priority areas involving complex and interdependent social systems (soc).
This work builds on our research on the COntext INterchange (COIN) project, which focused on the integration of
diverse distributed heterogeneous information sources using ontologies, databases, context mediation algorithms,
and wrapper technologies to overcome information representational conflicts. The COIN approach makes it
substantially easier and more transparent for individual receivers (e.g., applications, users) to access and exploit
distributed sources. Receivers specify their desired context to reduce ambiguities in the interpretation of information
coming from heterogeneous sources. This approach significantly reduces the overhead involved in the integration of
multiple sources, improves data quality, increases the speed of integration, and simplifies maintenance in an
environment of changing source and receiver context - which will lead to an effective and novel distributed
information grid infrastructure. This research also builds on our Global System for Sustainable Development
(GSSD), an Internet platform for information generation, provision, and integration of multiple domains, regions,
languages, and epistemologies relevant to international relations and national security.
(2) National Priority Studies: To experiment with and test the developed theory and technologies on practical
problems of data integration in national priority areas. Particular focus will be on national and homeland security,
including data sources about conflict and war, modes of instability and threat, international and regional
demographic, economic, and military statistics, money flows, and contextualizing terrorism defense and response.
Although LIGHT will leverage the results of our successful prior research projects, this will be the first research
effort to simultaneously and effectively address ontological and temporal information conflicts as well as
dramatically enhance information quality. Addressing problems of national priorities in such rapidly changing
complex environments requires extraction of observations from disparate sources, using different interpretations, at
different points in times, for different purposes, with different biases, and for a wide range of different uses and
users. This research will focus on integrating information both over individual domains and across multiple domains.
Another innovation is the concept and implementation of Collaborative Domain Spaces (CDS), within which
applications in a common domain can share, analyze, modify, and develop information. Applications also can span
multiple domains via Linked CDSs. The PIs have considerable experience with these research areas and the
organization and management of such large scale international and diverse research projects.
The PIs come from three different Schools at MIT: Management, Engineering, and Humanities, Arts & Social
Sciences. The faculty and graduate students come from about a dozen nationalities and diverse ethnic, racial, and
religious backgrounds. The currently identified external collaborators come from over 20 different organizations and
many different countries, industrial as well as developing. Specific efforts are proposed to engage even more
women, underrepresented minorities, and persons with disabilities.
The anticipated results apply to any complex domain that relies on heterogeneous distributed data to address and
resolve compelling problems. This initiative is supported by international collaborators from (a) scientific and
research institutions, (b) business and industry, and (c) national and international agencies. Research products
include: a System for Harmonized Information Processing (SHIP), a software platform, and diverse applications in
research and education which are anticipated to significantly impact the way complex organizations, and society in
general, understand and manage critical challenges in NHS, ECS, and ASE
Graphical modelling of modular machines
This research is aimed at advancing machine design through specifying and implementing
(in "proof of concept" form) a set of tools which graphically model modular machines.
The tools allow mechanical building elements (or machine modules) to be selected and
configured together in a highly flexible manner so that operation of the chosen configuration
can be simulated and performance properties evaluated. Implementation of the tools
has involved an extension in capability of a proprietary robot simulation system. This research has resulted in a general approach to graphically modelling manufacturing machines
built from modular elements.
A focus of study has been on a decomposition of machine functionality leading to the establishment
of a library of modular machine primitives. This provides a useful source of
commonly required machine building elements for use by machine designers. Study has
also focussed on the generation of machine configuration tools which facilitate the construction
of a simulation model and ultimately the physical machine itself. Simulation aspects
of machine control are also considered which depict methods of manipulating a
machine model in the simulation phase. In addition methods of achieving machine programming
have been considered which specify the machine and its operational tasks.
Means of adopting common information data structures are also considered which can facilitate
interfacing with other systems, including the physical machine system constructed
as an issue of the simulation phase. Each of these study areas is addressed in its own context,
but collectively they provide a means of creating a complete modular machine design
environment which can provide significant assistance to machine designers.
Part of the methodology employed in the study is based on the use of the discrete event
simulation technique. To easily and effectively describe a modular machine and its activity
in a simulation model, a hierarchical ring and tree data structure has been designed and
implemented. The modularity and reconfigurability are accommodated by the data structure,
and homogeneous transformations are adopted to determine the spatial location and
orientation of each of the machine elements.
A three-level machine task programming approach is used to describe the machine's activities.
A common data format method is used to interface the machine design environment
with the physical machine and other building blocks of manufacturing systems (such as
CAD systems) where systems integration approaches can lead to enhanced product realisation.
The study concludes that a modular machine design environment can be created by employing
the graphical simulation approach together with a set of comprehensive configuration.
tools. A generic framework has been derived which outlines the way in which
machine design environments can be constructed and suggestions are made as to how the
proof of concept design environment implemented in this study can be advanced
Management: A bibliography for NASA managers
This bibliography lists 653 reports, articles and other documents introduced into the NASA scientific and technical information system in 1987. Items are selected and grouped according to their usefulness to the manager as manager. Citiations are grouped into ten subject categories; human factors and personnel issues; management theory and techniques; industrial management and manufacturing; robotics and expert systems; computers and information management; research and development; economics, costs and markets; logistics and operations management, reliability and quality control; and legality, legislation, and policy
An Expressive Language and Efficient Execution System for Software Agents
Software agents can be used to automate many of the tedious, time-consuming
information processing tasks that humans currently have to complete manually.
However, to do so, agent plans must be capable of representing the myriad of
actions and control flows required to perform those tasks. In addition, since
these tasks can require integrating multiple sources of remote information ?
typically, a slow, I/O-bound process ? it is desirable to make execution as
efficient as possible. To address both of these needs, we present a flexible
software agent plan language and a highly parallel execution system that enable
the efficient execution of expressive agent plans. The plan language allows
complex tasks to be more easily expressed by providing a variety of operators
for flexibly processing the data as well as supporting subplans (for
modularity) and recursion (for indeterminate looping). The executor is based on
a streaming dataflow model of execution to maximize the amount of operator and
data parallelism possible at runtime. We have implemented both the language and
executor in a system called THESEUS. Our results from testing THESEUS show that
streaming dataflow execution can yield significant speedups over both
traditional serial (von Neumann) as well as non-streaming dataflow-style
execution that existing software and robot agent execution systems currently
support. In addition, we show how plans written in the language we present can
represent certain types of subtasks that cannot be accomplished using the
languages supported by network query engines. Finally, we demonstrate that the
increased expressivity of our plan language does not hamper performance;
specifically, we show how data can be integrated from multiple remote sources
just as efficiently using our architecture as is possible with a
state-of-the-art streaming-dataflow network query engine
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