Stochastic approach on a simplified OCC model for uncertainty and believability.
ABSTRACT As robots step into the human's daily lives, interaction and communication between human and robot is becoming essential. For this social interaction with humans, we propose an emotion generation model considering simplicity, believability and uncertainty. First, OCC model is simplified and then stochastic approach on emotion decision algorithm for believability and uncertainty is applied. The proposed model is implemented on a 3D robot expression simulator that can express emotions through its facial expression, gesture, led and so on. A demo of the model is provided as a result.
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ABSTRACT: Bayesian Networks are an important area of research and application within the domain of Artificial Intelligence. This paper explores the nature and implications for Bay esian Networks beginning with an overview and comparison of inferential statistics with Bayes’ Theorem. The nature, relevance and applicability of Bayesian Network theory for issues of advanced computability form the core of the current discussion. A number of current applications using Bayesian networks are examined. The paper concludes with a brief discussion of the appropriateness and limitations of Bayesian Networks for human-computer interaction and automated learning.10/2008: pages 117-130;
Conference Paper: A Robot Emotion Generation Mechanism Based on PAD Emotion Space.[Show abstract] [Hide abstract]
ABSTRACT: A robot emotion generation mechanism is presented in this paper, in which emotion is described in PAD emotion space. In this mechanism, emotion is affected by the robot personality, the robot task and the emotion origin, so the robot emotion will change naturally when it senses the extern stimuli. We also experiment on Fuwa robot, and demonstrate that this mechanism can make the robot’s emotion change be more easily accepted by people and is good for human-robot interaction.Intelligent Information Processing IV, 5th IFIP International Conference on Intelligent Information Processing, October 19-22, 2008, Beijing, China; 01/2008
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ABSTRACT: This paper has proposed a method of implementing humanlike motions by mapping their three-dimensional appearance to the android using a motion capture system. By measuring the android's posture and comparing it to the posture of a human subject, we propose a new method to evaluate motion sequences along bodily surfaces. Unlike other approaches that focus on reducing joint angle errors, we consider how to evaluate differences in the android's apparent motion, that is, motion at its visible surfaces. The experimental results show the effectiveness of the evaluation: the method can transfer human motion. However, the method is restricted by the speed of the motion. We have to introduce a method to deal with the dynamic characteristics (Ben=Amor et al., 2007) and physical limitations of the android. We also have to evaluate the method with different subjects. We would expect to generate the most natural and accurate movements using a female subject who is about the same height as the original woman on which the android is based. Moreover, we have to evaluate the human likeness of the visible motions by the subjective impressions the android gives experimental subjects and the responses it elicits, such as eye contact (Minato et al., 2006; Shimada et al., 2006), autonomic responses, and so on. Research in these areas is in progress.Humanoid Robots, Human-like Machines, 06/2007; , ISBN: 978-3-902613-07-3