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Human Centered Robotic Systems must be able to interact with humans such that the burden of adaptation lies with the machine and not with the human. This book collates a set of prominent papers presented during a two-day conference on "Human Centered Robotic Systems" held on November 19-20, 2009, in Bielefeld University, Germany. The aim of the conference was to bring together researchers from the areas of robotics, computer science, psychology, linguistics, and biology who are all focusing on a shared goal of cognitive interaction. A survey of recent approaches, the current state-of-the-art, and possible future directions in this interdisciplinary field is presented. It provides practitioners and scientists with an up-to-date introduction to this dynamic field, with methods and solutions that are likely to significantly impact on our future lives.
Figure 1.1. An outdoor scene "A bus is passing three cars which are parking between trees at the side of the road. Houses having two storeys are lined up at the street. 3 4 Introduction Figure 1.2. An assembly scene There seems to be a small open place between the group of houses in the foreground and the store in the background." In such or a similar way the content of the natural scene shown above can be described. It is quite easy to give such a short description. The problem is somewhat more complex for the second image. First of all, it can be stated that the image does not show an everyday scene. It appears as a kind of man made surrounding. But everyone can accept the following statements about this image: 1. The image shows a snapshot of an assembly line. 2. The robot in front is screwing. 3. There is no person in the working area of the robots. 4. All objects on the conveyor belt are worked on by robots. There are no free objects on the belt.
Human Centered Robotic Systems must be able to interact with humans such that the burden of adaptation lies with the machine and not with the human. This book collates a set of prominent papers presented during a two-day conference on "Human Centered Robotic Systems" held on November 19-20, 2009, in Bielefeld University, Germany. The aim of the conference was to bring together researchers from the areas of robotics, computer science, psychology, linguistics, and biology who are all focusing on a shared goal of cognitive interaction. A survey of recent approaches, the current state-of-the-art, and possible future directions in this interdisciplinary field is presented. It provides practitioners and scientists with an up-to-date introduction to this dynamic field, with methods and solutions that are likely to significantly impact on our future lives.
Following the highly successful International Conference on Computer Vision - stems held in Las Palmas, Spain (ICVS'99), this second International Workshop on Computer Vision Systems, ICVS 2001 was held as an associated workshop of the International Conference on Computer Vision in Vancouver, Canada. The organization of ICVS'99 and ICVS 2001 was motivated by the fact that the - jority of computer vision conferences focus on component technologies. However, Computer Vision has reached a level of maturity that allows us not only to p- form research on individual methods and system components but also to build fully integrated computer vision systems of signi cant complexity. This opens a number of new problems related to system architecture, methods for system synthesis and veri cation, active vision systems, control of perception and - tion, knowledge and system representation, context modeling, cue integration, etc. By focusing on methods and concepts for the construction of fully integrated vision systems, ICVS aims to bring together researchers interested in computer vision systems. Similar to the previous event in Las Palmas, ICVS 2001 was organized as a single-track workshop consisting of high-quality, previously unpublished papers on new and original research on computer vision systems. All contributions were presented orally. A total of 32 papers were submitted and reviewed thoroughly by program committee members. Twenty of them have been selected for p- sentation. We would like to thank all members of the organizing and program committee for their help in putting together a high-quality workshop.
Figure 1.1. An outdoor scene "A bus is passing three cars which are parking between trees at the side of the road. Houses having two storeys are lined up at the street. 3 4 Introduction Figure 1.2. An assembly scene There seems to be a small open place between the group of houses in the foreground and the store in the background". In such or a similar way the content of the natural scene shown above can be described. It is quite easy to give such a short description. The problem is somewhat more complex for the second image. First of all, it can be stated that the image does not show an everyday scene. It appears as a kind of man made surrounding. But everyone can accept the following statements about this image: 1. The image shows a snapshot of an assembly line. 2. The robot in front is screwing. 3. There is no person in the working area of the robots. 4. All objects on the conveyor belt are worked on by robots. There are no free objects on the belt.
Nach Paderborn 1986 findet das DAGM-Symposium zum zweiten Male in Ost- westfalen statt. Es ist mir eine Freude, nach fiinfjli.hrigem Bestehen der Techni- schen Fakultat der Universitat Bielefeld das 17. DAGM-Symposium ausrichten zu konnen. Dies umso mehr, da erstmalig die deutsche Mustererkennungsta- gung und die KI-Konferenz zusammen an einem Ort in zeitlicher Abstimmung durchgefiihrt werden. Die Organisatoren beider Tagungen wlinschen sich, daB ein intensiver Diskurs zwischen den beiden verwandten Disziplinen einsetzen wird. Mit dem Schwerpunktthema "Verstehen akustischer und visueller Informa- tionen" sind mehrere Intentionen verbunden. Zum einen werden die klassischen Problemfelder der Mustererkennung, die Auswertung von Bild- und Sprachsi- gnalen, in das Zentrum der diesjli.hrigen Tagung gerlickt. "Verstehen" ist die Aufgabenstellung, die eine Brlicke zwischen Mustererkennung und klinstlicher Intelligenz schlagen kann. Eine weitere enge Beziehung ergibt sich zum Sonder- forschungsbereich 360 "Situierte Klinstliche Kommunikatoren", der als gemein- same Unternehmung der Technischen Fakultat und der Fakultat fiir Linguistik und Literaturwissenschaften 1993 an der Universitat Bielefeld gegrlindet wurde.
In den letzten Jahren hat eine Verlagerung des Einsatzes von Rechenanlagen von der Daten- zur Wissensverarbeitung eingesetzt. Wah rend Daten, vereinfacht gespro- chen, im wesentlichen durch alphanumerische Zeichenfolgen reprasentiert werden, die zum Beispiel in Feldern und Records strukturiert sind und die bestimmte isolierte Eigenschaften eines Problemkreises enthalten, versteht man unter Wissen vielfaltig miteinander assoziierte reichhaltige symbolische Strukturen, die in expliziter Form die relevanten Fakten und Handlungsanweisungen eines komplexen Problemkreises reprasentieren. Wissensverarbeitung umfa6t den Erwerb, die Reprasentation und die Nutzung des zur Losung eines bestimmten Aufgabenkomplexes erforderlichen deklarati- yen und prozeduralen Wissens. Ganz entsprechend haben in der Mustererkennung die Wissensverarbeitung und die wissensbasierten Systeme zur Bild- und Sprachanalyse zunehmendes Interesse gefunden, letztlich deshalb, weil den gestiegenen Anforderun- gen an mustererkennende Systeme nur so entsprochen werden kann. In der hier von Herrn Sagerer vorgelegten Dissertation wird ein realisiertes und einsatzfahiges wissensbasiertes System zur diagnostischen Interpretation nuklear- medizinischer Sequenzszintigramme des schlagenden menschlichen Herzens beschrieben. An dem relativ umfangreichen System haben mehrere Personen gearbeitet. Der wesentli- che Beitrag des Autors ist die Entwicklung und Realisierung eines allgemein nutzba- ren und leistungsfahigen Formalismus zur Wissensreprasentation, die Erarbeitung, Strukturierung und Eingabe des fur den erwahnten Problemkreis erforderlichen Wissens, die Realisierung eines ebenfalls allgemein einsetzbaren modellgetriebenen Kontroll- algorithmus auf der Basis des A*-Graphsuchalgorithmus sowie schlie6lich die Integra- tion der entwickelten Moduln zu einer ersten lauffahigen Systemversion. Abgesehen von der Systemrealisierung liegt auf den erwahnten Punkten der chwerpunkt der Dar- stellung.
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