Alle Publikationen
- <<
- <
- 1
2019
-
(2019): Culture as a Sensor? A Novel Perspective on Human Activity Recognition. In: International Journal of Social Robotics 11 (5), S. 797-814. DOI: 10.1007/s12369-019-00590-3
DOI: https://doi.org/10.1007/s12369-019-00590-3 Abstract: Human Activity Recognition (HAR) systems are devoted to identifying, amidst the sensory stream provided by one or more sensors located so that they can monitor the actions of a person, portions related to the execution of a number of a-priori defined activities of interest. Improving the performance of systems for Human Activity Recognition is a long-standing research goal: solutions include more accurate sensors, more sophisticated algorithms for the extraction and analysis of relevant information from the sensory data, and the enhancement of the sensory analysis with general or person-specific knowledge about the execution of the activities of interest. Following the latter trend, in this article we propose the association and enhancement of the sensory data analysis with cultural information, that can be seen as an estimate of person-specific information, relieved of the burden of a long/complex setup phase. We propose a culture-aware Human Activity Recognition system which associates the recognition response provided by a state-of-the-art, culture-unaware HAR system with culture-specific information about where and when activities are most likely performed in different cultures, encoded in an ontology. The merging of the cultural information with the culture-unaware responses is done by a Bayesian Network, whose probabilistic approach allows for avoiding stereotypical representations. Experiments performed offline and online, using images acquired by a mobile robot in an apartment, show that the culture-aware HAR system consistently outperforms the culture-unaware HAR system.
-
(2019): Understanding of Human Behavior with a Robotic Agent Through Daily Activity Analysis. In: International Journal of Social Robotics 11 (3), S. 437-462. DOI: 10.1007/s12369-019-00513-2
DOI: https://doi.org/10.1007/s12369-019-00513-2 Abstract: Personal assistive robots to be realized in the near future should have the ability to seamlessly coexist with humans in unconstrained environments, with the robot’s capability to understand and interpret the human behavior during human–robot cohabitation significantly contributing towards this end. Still, the understanding of human behavior through a robot is a challenging task as it necessitates a comprehensive representation of the high-level structure of the human’s behavior from the robot’s low-level sensory input. The paper at hand tackles this problem by demonstrating a robotic agent capable of apprehending human daily activities through a method, the Interaction Unit analysis, that enables activities’ decomposition into a sequence of units, each one associated with a behavioral factor. The modelling of human behavior is addressed with a Dynamic Bayesian Network that operates on top of the Interaction Unit, offering quantification of the behavioral factors and the formulation of the human’s behavioral model. In addition, light-weight human action and object manipulation monitoring strategies have been developed, based on RGB-D and laser sensors, tailored for onboard robot operation. As a proof of concept, we used our robot to evaluate the ability of the method to differentiate among the examined human activities, as well as to assess the capability of behavior modeling of people with Mild Cognitive Impairment. Moreover, we deployed our robot in 12 real house environments with real users, showcasing the behavior understanding ability of our method in unconstrained realistic environments. The evaluation process revealed promising performance and demonstrated that human behavior can be automatically modeled through Interaction Unit analysis, directly from robotic agents.
2017
-
(2017): Sociality and Normativity for Robots. Philosophical Inquiries into Human-Robot Interactions. Cham: Springer International Publishing (Studies in the Philosophy of Sociality). Online verfügbar unter https://ebookcentral.proquest.com/lib/gbv/detail.action?docID=4867905
Abstract: This volume offers eleven philosophical investigations into our futurerelations with social robots--robots that are specially designed to engage andconnect with human beings.The contributors present cutting edge research thatexamines whether, and on which terms, robots can become members ofhuman societies. Can our relations to robots be said to be 'social'?Can robots enter into normative relationships with human beings? Howwill human social relations change when we interact with robots atwork and at home?The authors of this volume explore these questions from theperspective of philosophy, cognitive science, psychology, androbotics. The first three chapters offer a taxonomy for the classificationof simulated social interactions, investigate whether human socialinteractions with robots can be genuine, and discuss the significanceof social relations for the formation of human individuality.Subsequent chapters clarify whether robots could be said to actuallyfollow social norms, whether they could live up to the socialmeaning of care in caregiving professions, and how we will need toprogram robots so that they can negotiate the conventions of humansocial space and collaborate with humans. Can we perform jointactions with robots, where both sides need to honour commitments, andhow will such new commitments and practices change our regionalcultures?The authors connect research in social robotics andempirical studies in Human-Robot Interaction to recent debates insocial ontology, social cognition, as well as ethics and philosophy oftechnology.The book is a response to the challenge that social robotics presentsfor our traditional conceptions of social interaction, whichpresuppose such essential capacities as consciousness, intentionality,agency, and normative understanding. The authors develop insightfulanswers along new interdisciplinarypathways in 'robophilosophy,' a new research area that will help us toshape the 'robot revolution,' the distinctive technological change ofthe beginning 21st century. Raul Hakli (PhD) studied philosophy and computer science at theUniversity of Helsinki, Finland. He received his PhD in theoreticalphilosophy in 2010. While editing the book he was Associate Professorat the Aarhus University, Denmark. Currently he works as a researcherat the University of Helsinki, Finland. His research interests includesocial ontology, collective intentionality, epistemology, philosophyof social robotics, and philosophy of the social sciences. Johanna Seibt (PhD. at the Univ of Pittsburg, USA; Dr. phil. habil. atthe Univ of Konstanz, Germany) is Professor for Applied ProcessOntology and Integrative Social Robotics, Aarhus University, Denmark;previously she taught at the Univ of Texas at Austin, USA. Her mainresearch area is in analytical ontology and metaphysics. More recentlyshe works also in philosophy of social robotics. She is head of theResearch Unit for Robophilosophy at the School for Culture and Society, Aarhus University, which conducts interdisciplinaryHumanities research of and in social robotics and coordinates theinternational Research Network for Transdisciplinary Studies in SocialRobotics (TRANSOR).
2016
-
(2016): Anticipating Human Activities Using Object Affordances for Reactive Robotic Response. In: IEEE transactions on pattern analysis and machine intelligence 38 (1), S. 14-29. DOI: 10.1109/TPAMI.2015.2430335
DOI: http://www.ncbi.nlm.nih.gov/pubmed/26656575 Abstract: An important aspect of human perception is anticipation, which we use extensively in our day-to-day activities when interacting with other humans as well as with our surroundings. Anticipating which activities will a human do next (and how) can enable an assistive robot to plan ahead for reactive responses. Furthermore, anticipation can even improve the detection accuracy of past activities. The challenge, however, is two-fold: We need to capture the rich context for modeling the activities and object affordances, and we need to anticipate the distribution over a large space of future human activities. In this work, we represent each possible future using an anticipatory temporal conditional random field (ATCRF) that models the rich spatial-temporal relations through object affordances. We then consider each ATCRF as a particle and represent the distribution over the potential futures using a set of particles. In extensive evaluation on CAD-120 human activity RGB-D dataset, we first show that anticipation improves the state-of-the-art detection results. We then show that for new subjects (not seen in the training set), we obtain an activity anticipation accuracy (defined as whether one of top three predictions actually happened) of 84.1, 74.4 and 62.2 percent for an anticipation time of 1, 3 and 10 seconds respectively. Finally, we also show a robot using our algorithm for performing a few reactive responses.
Keywords: Affordance, affordances, Affordanz, Algorithms, Aniticipation, Human Activities, Humans, Imaging, Intentionserkennung (Roboter erkennt Menschenintention), J. J. Gibson's theory of affordance, machine learning, MODELS, Movement, PERCEPTION, Psychological, Robotics, Soziosensitive Systeme, Soziosensitivität, Statistical, Three-Dimensional, Video Recording 2014
-
(2014): Romeo2 Project: Humanoid Robot Assistant and Companion for Everyday Life. I. Situation Assessment for Social Intelligence. In: Artificial Intelligence and Cognition, S. 140-147. Online verfügbar unter https://hal.archives-ouvertes.fr/hal-01096094
Abstract: For a socially intelligent robot, different levels of situation as-sessment are required, ranging from basic processing of sensor input tohigh-level analysis of semantics and intention. However, the attempt tocombine them all prompts new research challenges and the need of a co-herent framework and architecture.This paper presents the situation assessment aspect of Romeo2, a uniqueproject aiming to bring multi-modal and multi-layered perception on asingle system and targeting for a unified theoretical and functional frame-work for a robot companion for everyday life. It also discusses some of theinnovation potentials, which the combination of these various perceptionabilities adds into the robot’s socio-cognitive capabilities.
2013
-
(2013) : Hey! There is someone at your door. A hearing robot using visual communication signals of hearing dogs to communicate intent: 2013 IEEE Symposium on Artificial Life (ALIFE): 16-19 April 2013, Singapore ; [part of the] 2013 IEEE Symposium Series on Computational Intelligence (SSCI): 2013 IEEE Symposium on Artificial Life (ALife): Singapore, Singapore: 4/16/2013 - 4/19/2013. Annual IEEE Computer Conference; IEEE Symposium on Artificial Life; Alife; IEEE Symposium Series on Computational Intelligence; Ssci: Piscataway, NJ: IEEE, S. 90-97
Abstract: This paper presents a study of the readability of dog-inspired visual communication signals in a human-robot interaction scenario. This study was motivated by specially trained hearing dogs which provide assistance to their deaf owners by using visual communication signals to lead them to the sound source. For our human-robot interaction scenario, a robot was used in place of a hearing dog to lead participants to two different sound sources. The robot was preprogrammed with dog-inspired behaviors, controlled by a wizard who directly implemented the dog behavioral strategy on the robot during the trial. By using dog-inspired visual communication signals as a means of communication, the robot was able to lead participants to the sound sources (the microwave door, the front door). Findings indicate that untrained participants could correctly interpret the robot's intentions. Head movements and gaze directions were important for communicating the robot's intention using visual communication signals.
2002
-
(2002): From embodied to socially embedded agents – Implications for interaction-aware robots. In: COGNITIVE SYSTEMS RESEARCH 3 (3), S. 397-428. DOI: 10.1016/S1389-0417(02)00050-5
DOI: https://doi.org/10.1016/S1389-0417(02)00050-5 Abstract: First, this article proposes a minimal definition of embodiment that can be applied across animals and artefacts. We discuss the potential contributions of this operational definition with respect to assessing and measuring the degree of embodiment in different biological and artificial systems. Second, we outline how this definition can be extended to lead to the particular notion of social embeddedness. Socially embedded agents are structurally coupled with their social environment, in that their sensorimotor activity is grounded in the social environment that the agent is surrounded by. Lastly, based on research in the social sciences on human–human interaction, we discuss perceptual requirements for interaction-aware robotic agents—agents whose identification and interpretation of the (social) environment is facilitated by awareness of the structure of agent–agent interactions (including humans ‘in the loop’). We suggest relevant concepts and heuristics that can contribute to studies of degrees of embodiment of robots that interact with social environments. Manipulating and systematically investigating these heuristics permits variation of the degree of embodiment of such interaction-aware robots.
- <<
- <
- 1