PERUSE: An Unsupervised Algorithm for Finding Recurrig Patterns in Time Series
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Probabilistic discovery of time series motifs
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
IEA/AIE'2004 Proceedings of the 17th international conference on Innovations in applied artificial intelligence
A generic motif discovery algorithm for sequential data
Bioinformatics
Multivariate out-of-sample tests for Granger causality
Computational Statistics & Data Analysis
A survey of robot learning from demonstration
Robotics and Autonomous Systems
Improving activity discovery with automatic neighborhood estimation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A Fuzzy Qualitative Framework for Connecting Robot Qualitative and Quantitative Representations
IEEE Transactions on Fuzzy Systems
Towards conversational artifacts
AMT'11 Proceedings of the 7th international conference on Active media technology
Towards conversational artifacts
BI'11 Proceedings of the 2011 international conference on Brain informatics
IUKM'11 Proceedings of the 2011 international conference on Integrated uncertainty in knowledge modelling and decision making
Social intelligence design for knowledge circulation
DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
CPMD: a matlab toolbox for change point and constrained motif discovery
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
G-SteX: greedy stem extension for free-length constrained motif discovery
IEA/AIE'12 Proceedings of the 25th international conference on Industrial Engineering and Other Applications of Applied Intelligent Systems: advanced research in applied artificial intelligence
Learning-based modeling of multimodal behaviors for humanlike robots
Proceedings of the 2014 ACM/IEEE international conference on Human-robot interaction
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Human-Robot Interaction using free hand gestures is gaining more importance as more untrained humans are operating robots in home and office environments. The robot needs to solve three problems to be operated by free hand gestures: gesture (command) detection, action generation (related to the domain of the task) and association between gestures and actions. In this paper we propose a novel technique that allows the robot to solve these three problems together learning the action space, the command space, and their relations by just watching another robot operated by a human operator. The main technical contribution of this paper is the introduction of a novel algorithm that allows the robot to segment and discover patterns in its perceived signals without any prior knowledge of the number of different patterns, their occurrences or lengths. The second contribution is using a Ganger-Causality based test to limit the search space for the delay between actions and commands utilizing their relations and taking into account the autonomy level of the robot. The paper also presents a feasibility study in which the learning robot was able to predict actor's behavior with 95.2% accuracy after monitoring a single interaction between a novice operator and a WOZ operated robot representing the actor.