Alle Publikationen

  • Erweiterte Suche öffnen

Treffer: 2
  • <<
  • 1

  • 2015

  • Nigam, Aastha; Riek, Laurel D. (2015) : Social context perception for mobile robots In: Burgard, Wolfram: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Sept. 28, 2015 - Oct. 2, 2015, Hamburg, Germany: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS): Hamburg, Germany: 9/28/2015 - 10/2/2015. IEEE/RSJ International Conference on Intelligent Robots and Systems; Iros: Piscataway, NJ: IEEE, S. 3621-3627

    Abstract: As robots enter human spaces, unique perception challenges are emerging. Sensing human activity, adapting to highly dynamic environments, and acting coherently and contingently is challenging when robots transition from structured environments to human-centric ones. We approach this problem by employing context-based perception, a biologically-inspired, low-cost approach to sensing that leverages noisy, global features. Across several months, our mobile robot collected real-world, multimodal data from multi-use locations; where the same space might be used for many different activities. We then ran a series of unimodal and multimodal classification experiments. We successfully classified several aspects of situational context from noisy data, and, to our knowledge are the first group to do so. This work represents an important step toward enabling robots that can readily leverage context to solve perceptual tasks.

    Keywords: context-based perception, Favoriten, HSE, Human Activity Recognition, human social environments, human-centric, Intentionserkennung (Roboter erkennt Menschenintention), Mobile Roboter, SITUATION, sozialer Kontext, Sozialkontext

  • 2001

  • Prendinger, H.; Ishizuka, M. (2001): Let's talk!. Socially intelligent agents for language conversation training. In: IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans 31 (5), S. 465-471. DOI: 10.1109/3468.952722

    Abstract: This paper promotes socially intelligent animated agents for the pedagogical task of English conversation training for native speakers of Japanese. Since student-agent conversations are realized as role-playing interactions, strong requirements are imposed on the agents' affective and social abilities. As a novel feature, social role awareness is introduced to animated conversational agents, that are by now strong affective reasoners, but otherwise often lack the social competence observed in humans. In particular, humans may easily adjust their behavior depending on their respective role in a social setting, whereas their synthetic pendants tend to be driven mostly by emotions and personality. Our main contribution is the incorporation of a "social filter program" to mental models of animated agents. This program may qualify an agent's expression of its emotional state by the social context, thereby enhancing the agent's believability as a conversational partner. Our implemented system is web-based and demonstrates socially aware animated agents in a virtual coffee shop environment. An experiment with our conversation system shows that users consider socially aware agents as more natural than agents that violate conventional practices.

    Keywords: Adaptive Systeme, Agent, Computerwissenschaft, doppelter Treffer, Emotions, emotionssensitiv, Favoriten, Ingenieurswissenschaft, Interaktion, Kommunikation, Künstliche Intelligenz, Linguistik, Mensch-Technik-Relationen (MTR), Modelle/Theorien, Realtechnik, social filter program, social filter program for animated agents, Soziale Angemessenheit, soziale intelligente Agenten, sozialer Kontext, Sozialkompetenz, Soziosensitive Systeme, Spracherwerb, Teaching, Sprachverstehen, Technik, training in social competences, Volltreffer
  • <<
  • 1