5 research outputs found
The Cyborg Astrobiologist: Testing a Novelty-Detection Algorithm on Two Mobile Exploration Systems at Rivas Vaciamadrid in Spain and at the Mars Desert Research Station in Utah
(ABRIDGED) In previous work, two platforms have been developed for testing
computer-vision algorithms for robotic planetary exploration (McGuire et al.
2004b,2005; Bartolo et al. 2007). The wearable-computer platform has been
tested at geological and astrobiological field sites in Spain (Rivas
Vaciamadrid and Riba de Santiuste), and the phone-camera has been tested at a
geological field site in Malta. In this work, we (i) apply a Hopfield
neural-network algorithm for novelty detection based upon color, (ii) integrate
a field-capable digital microscope on the wearable computer platform, (iii)
test this novelty detection with the digital microscope at Rivas Vaciamadrid,
(iv) develop a Bluetooth communication mode for the phone-camera platform, in
order to allow access to a mobile processing computer at the field sites, and
(v) test the novelty detection on the Bluetooth-enabled phone-camera connected
to a netbook computer at the Mars Desert Research Station in Utah. This systems
engineering and field testing have together allowed us to develop a real-time
computer-vision system that is capable, for example, of identifying lichens as
novel within a series of images acquired in semi-arid desert environments. We
acquired sequences of images of geologic outcrops in Utah and Spain consisting
of various rock types and colors to test this algorithm. The algorithm robustly
recognized previously-observed units by their color, while requiring only a
single image or a few images to learn colors as familiar, demonstrating its
fast learning capability.Comment: 28 pages, 12 figures, accepted for publication in the International
Journal of Astrobiolog
Universal Science of Mind: Can Complexity-Based Artificial Intelligence Save the World in Crisis?
While practical efforts in the field of artificial intelligence grow exponentially, the truly scientific and mathematically exact understanding of the underlying phenomena of intelligence and consciousness is still missing in the conventional science framework. The inevitably dominating empirical, trial-and-error approach has vanishing efficiency for those extremely complicated phenomena, ending up in fundamentally limited imitations of intelligent behaviour. We provide the first-principle analysis of unreduced many-body interaction process in the brain revealing its qualitatively new features, which give rise to rigorously defined chaotic, noncomputable, intelligent and conscious behaviour. Based on the obtained universal concepts of unreduced dynamic complexity, intelligence and consciousness, we derive the universal laws of intelligence applicable to any kind of intelligent system interacting with the environment. We finally show why and how these fundamentally substantiated and therefore practically efficient laws of intelligent system dynamics are indispensable for correct AI design and training, which is urgently needed in this time of critical global change towards the truly sustainable development
A Posture Sequence Learning System for an Anthropomorphic Robotic Hand
The paper presents a cognitive architecture for posture learning of an anthropomorphic robotic hand. Our approach is aimed to allow the robotic system to perform complex perceptual operations, to interact with a human user and to integrate the perceptions by a cognitive representation of the scene and the observed actions. The anthropomorphic robotic hand imitates the gestures acquired by the vision system in order to learn meaningful movements, to build its knowledge by different conceptual spaces and to perform complex interaction with the human operator
Proceedings / 17. Workshop Computational Intelligence [Elektronische Ressource] : Dortmund, 5. - 7. Dezember 2007
Dieser Tagungsband enthĂ€lt die BeitrĂ€ge des 17. Workshops âComputational Intelligenceâ des Fachausschusses 5.14 der VDI/VDE-Gesellschaft fĂŒr Mess- und Automatisierungstechnik (GMA) und der Fachgruppe âFuzzy-Systeme und Soft-Computingâ der Gesellschaft fĂŒr Informatik (GI), der vom 5. â 7. Dezember 2007 im Haus Bommerholz bei Dortmund stattfindet. Der GMA-Fachausschuss 5.14 âComputational Intelligenceâ entstand 2005 aus den bisherigen FachausschĂŒssen âNeuronale Netze und EvolutionĂ€re Algorithmenâ (FA 5.21) sowie âFuzzy Controlâ (FA 5.22). Der Workshop steht in der Tradition der bisherigen Fuzzy-Workshops, hat aber seinen Fokus in den letzten Jahren schrittweise erweitert. Die Schwerpunkte sind Methoden, Anwendungen und Tools fĂŒr âą Fuzzy-Systeme, âą KĂŒnstliche Neuronale Netze, âą EvolutionĂ€re Algorithmen und âą Data-Mining-Verfahren sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen. INHALTSVERZEICHNIS T. Fober, E. HĂŒllermeier, M. Mernberger (Philipps-UniversitĂ€t Marburg): Evolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules G. Heidemann, S. Klenk (UniversitĂ€t Stuttgart): Visual Analytics for Image Retrieval F. RĂŒgheimer (OvG-UniversitĂ€t Magdeburg): A Condensed Representation for Distributions over Set-Valued Attributes T. Mrziglod (Bayer Technology Services GmbH, Leverkusen): Mit datenbasierten Technologien und Versuchsplanung zu erfolgreichen Produkten H. Schulte (Bosch Rexroth AG, Elchingen): Approximationsgenauigkeit und dynamisches Fehlerwachstum der Modellierung mit Takagi-Sugeno Fuzzy Systemen C. Burghart, R. Mikut, T. Asfour, A. Schmid, F. Kraft, O. Schrempf, H. Holzapfel, R. Stiefelhagen, A. Swerdlow, G. Bretthauer, R. Dillmann (UniversitĂ€t Karlsruhe, Forschungszentrum Karlsruhe GmbH): Kognitive Architekturen fĂŒr humanoide Roboter: Anforderungen, Ăberblick und Vergleich R. Mikut, C. Burghart, A. Swerdlow (Forschungszentrum Karlsruhe GmbH, UniversitĂ€t Karlsruhe): Ein Gedankenexperiment zum Entwurf einer integrierten kognitiven Architektur fĂŒr humanoide Roboter G. Milighetti, H.-B. Kuntze (FhG IITB Karlsruhe): Diskret-kontinuierliche Regelung und Ăberwachung von Robotern basierend auf Aktionsprimitiven und Petri-Netzen N. Rosemann, W. Brockmann (UniversitĂ€t OsnabrĂŒck): Kontrolle dynamischer Eigenschaften des Online-Lernens in Neuro-Fuzzy-Systemen mit dem SILKE-Ansatz A. Hans, D. SchneegaĂ, A. SchĂ€fer, S. Udluft (Siemens AG, TU Ilmenau): Sichere Exploration fĂŒr Reinforcement-Learning-basierte Regelung Th. Bartz-Beielstein, M. Bongards, C. Claes, W. Konen, H. Westenberger (FH Köln): Datenanalyse und Prozessoptimierung fĂŒr Kanalnetze und KlĂ€ranlagen mit CI-Methoden S. Nusser, C. Otte, W. Hauptmann (Siemens AG, OvG-UniversitĂ€t Magdeburg): Learning Binary Classifiers for Applications in Safety-Related Domains W. Jakob, A. Quinte, K.-U. Stucky, W. SĂŒĂ, C. Blume (Forschungszentrum Karlsruhe GmbH; FH Köln, Campus Gummersbach) Schnelles Resource Constrained Project Scheduling mit dem EvolutionĂ€ren Algorithmus GLEAM M. PreuĂ, B. Naujoks (UniversitĂ€t Dortmund): EvolutionĂ€re mehrkriterielle Optimierung bei Anwendungen mit nichtzusammenhĂ€ngenden Pareto-Mengen G. Rudolph, M. PreuĂ (UniversitĂ€t Dortmund): in mehrkriterielles Evolutionsverfahren zur Bestimmung des Phasengleichgewichts von gemischten FlĂŒssigkeiten Y. Chen, O. Burmeister, C. Bauer, R. Rupp, R. Mikut (UniversitĂ€t Karlsruhe, Forschungszentrum Karlsruhe GmbH, OrthopĂ€dische UniversitĂ€tsklinik Heidelberg): First Steps to Future Applications of Spinal Neural Circuit Models in Neuroprostheses and Humanoid Robots F. Hoffmann, J. Braun, T. Bertram, S. Hölemann (UniversitĂ€t Dortmund, RWTH Aachen): Multikriterielle Optimierung mit modellgestĂŒtzten Evolutionsstrategien S. Piana, S. Engell (UniversitĂ€t Dortmund): EvolutionĂ€re Optimierung des Betriebs von rohrlosen Chemieanlagen T. Runkler (Siemens AG, CT IC 4): Pareto Optimization of the Fuzzy câMeans Clustering Model Using a MultiâObjective Genetic Algorithm H. J. Rommelfanger (J.W. Goethe-UniversitĂ€t Frankfurt am Main): Die Optimierung von Fuzzy-Zielfunktionen in Fuzzy (Mehrziel-) LPSystemen - Ein kritischer Ăberblick D. Gamrad, D. Söffker (UniversitĂ€t Duisburg-Essen): Formalisierung menschlicher Interaktionen durch Situations-Operator- Modellbildung S. Ritter, P. Bretschneider (FhG AST Ilmenau): Optimale Planung und BetriebsfĂŒhrung der Energieversorgung im liberalisierten Energiemarkt R. Seising (Medizinische UniversitĂ€t Wien): Heinrich Hertz, Ludwig Wittgenstein und die Fuzzy-Strukturen - Eine kleine âBildergeschichteâ zur Erkenntnisphilosophie J. Limberg, R. Seising (Medizinische UniversitĂ€t Wien): Sequenzvergleiche im Fuzzy-Hypercube M. Steinbrecher, R. Kruse (OvG-UniversitĂ€t Magdeburg): Visualisierung temporaler AbhĂ€ngigkeiten in Bayesschen Netzen M. Schneider, R. Tillmann, U. Lehmann, J. Krone, P. Langbein, U. Stark, J. Schrickel, Ch. Ament, P. Otto (FH SĂŒdwestfalen, Airbus Deutschland GmbH, Hamburg, TU Ilmenau): KĂŒnstliches Neuronales Netz zur Analyse der Geometrie von groĂflĂ€chig gekrĂŒmmten Bauteilen C. Frey (FhG IITB Karlsruhe): Prozessdiagnose und Monitoring feldbusbasierter Automatisierungsanlagen mittels selbstorganisierender Karte