Intelligent Robotics and Communication Laboratories

Kyoto, Japan

Intelligent Robotics and Communication Laboratories

Kyoto, Japan

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Kim Y.-J.,KAIST | Lee J.-Y.,Intelligent Robotics and Communication Laboratories | Lee J.-J.,KAIST
2012 IEEE International Conference on Information and Automation, ICIA 2012 | Year: 2012

In this paper, we present a balance control strategy for a walking biped robot in an unexpected external applied force. We assume that a sudden lateral and longitudinal force could be applied at the center of the pelvis of the biped robot during walking with a walking trajectory which is predesigned in advance by considering the energy-efficiency. With this situation, an balance control strategy is investigated and suggested. The balance control strategy is divided into four successive actions. Firstly, the robot should be controlled for the ZMP(Zero Moment Point) to move to the center of its sole. Secondly, the robot moves its swing leg to make the height of the sole of its swing leg lower. Thirdly, the swing leg of robot is stretched. Fourthly, the stance leg is contracted to make the robot in the double support phase. To verify the suggested strategy, computer simulation is performed. © 2012 IEEE.


Heracleous P.,Intelligent Robotics and Communication Laboratories | Heracleous P.,CNRS GIPSA Laboratory | Beautemps D.,CNRS GIPSA Laboratory | Aboutabit N.,CNRS GIPSA Laboratory
Speech Communication | Year: 2010

This article discusses the automatic recognition of Cued Speech in French based on hidden Markov models (HMMs). Cued Speech is a visual mode which, by using hand shapes in different positions and in combination with lip patterns of speech, makes all the sounds of a spoken language clearly understandable to deaf people. The aim of Cued Speech is to overcome the problems of lipreading and thus enable deaf children and adults to understand spoken language completely. In the current study, the authors demonstrate that visible gestures are as discriminant as audible orofacial gestures. Phoneme recognition and isolated word recognition experiments have been conducted using data from a normal-hearing cuer. The results obtained were very promising, and the study has been extended by applying the proposed methods to a deaf cuer. The achieved results have not shown any significant differences compared to automatic Cued Speech recognition in a normal-hearing subject. In automatic recognition of Cued Speech, lip shape and gesture recognition are required. Moreover, the integration of the two modalities is of great importance. In this study, lip shape component is fused with hand component to realize Cued Speech recognition. Using concatenative feature fusion and multi-stream HMM decision fusion, vowel recognition, consonant recognition, and isolated word recognition experiments have been conducted. For vowel recognition, an 87.6% vowel accuracy was obtained showing a 61.3% relative improvement compared to the sole use of lip shape parameters. In the case of consonant recognition, a 78.9% accuracy was obtained showing a 56% relative improvement compared to the use of lip shape only. In addition to vowel and consonant recognition, a complete phoneme recognition experiment using concatenated feature vectors and Gaussian mixture model (GMM) discrimination was conducted, obtaining a 74.4% phoneme accuracy. Isolated word recognition experiments in both normal-hearing and deaf subjects were also conducted providing a word accuracy of 94.9% and 89%, respectively. The obtained results were compared with those obtained using audio signal, and comparable accuracies were observed. © 2010 Elsevier B.V. All rights reserved.


Heracleous P.,CNRS GIPSA Laboratory | Heracleous P.,Intelligent Robotics and Communication Laboratories | Tran V.-A.,CNRS GIPSA Laboratory | Nagai T.,Nara Institute of Science and Technology | Shikano K.,Nara Institute of Science and Technology
IEEE Transactions on Audio, Speech and Language Processing | Year: 2010

Non-audible murmur (NAM) is an unvoiced speech signal that can be received through the body tissue with the use of special acoustic sensors (i.e., NAM microphones) attached behind the talker's ear. The authors had previously reported experimental results for NAM recognition using a stethoscopic and a silicon NAM microphone. Using a small amount of training data from a single speaker and adaptation approaches, 93.9% of word accuracy was achieved for a 20 k Japanese vocabulary dictation task. In this paper, further analysis of NAM speech is made using distance measures between hidden Markov models (HMMs). It has been shown that owing to the reduced spectral space of NAM speech, the HMM distances are also reduced when compared with those of normal speech. In the case of Japanese vowels and fricatives, the distance measures in NAM speech follow the same relative inter-phoneme relationship as that in normal speech without significant differences. However, significant differences have been found in the case of Japanese plosives. More specifically, in NAM speech, the distances between voiced/unvoiced consonant pairs articulated in the same place drastically decreased. As a result, the inter-phoneme relationship as compared to normal-speech changed significantly, causing a substantial decrease in the recognition accuracy. A speaker-dependent phoneme recognition experiment has been conducted, obtained 81.5% NAM phoneme correct, showing a relationship between HMM distance measures and phoneme accuracy. In a NAM microphone, body transmission and loss of lip radiation act as a low-pass filter. As a result, higher frequency components are attenuated in a NAM signal. Because of spectral reduction, NAM's unvoiced nature, and the type of articulation, NAM sounds become similar, causing a larger number of confusions when compared with normal speech. Yet many of those sounds are visually different on face/mouth/lips, and the integration of visual information increases their discrimination. As a result, recognition accuracy increases as well. In this article, the visual information extracted from the talkers' facial movements is fused with NAM speech. The experimental results reveal a relative improvement of 10.5% on average when fused NAM speech and facial information were used compared with using only NAM speech. © 2010 IEEE.


Zanlungo F.,Intelligent Robotics and Communication Laboratories | Zanlungo F.,Japan Science and Technology Agency | Ikeda T.,Intelligent Robotics and Communication Laboratories | Ikeda T.,Japan Science and Technology Agency | And 2 more authors.
EPL | Year: 2011

We introduce a new specification of the social force model in which pedestrians explicitly predict the place and time of the next collision in order to avoid it. This and other specifications of the social force model are calibrated, using genetic algorithms, on a set of pedestrian trajectories, obtained tracking with laser range finders the movement of pedestrians in controlled experiments, and their performance is compared. The results show that the proposed method has a better performance in describing the trajectory set. © 2011 Europhysics Letters Association.


Heracleous P.,Intelligent Robotics and Communication Laboratories | Hagita N.,Intelligent Robotics and Communication Laboratories
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings | Year: 2011

This article introduces automatic recognition of speech without any audio information. Movements of the tongue, lips, and jaw are tracked by an Electro-Magnetic Articulography (EMA) device and are used as features to create hidden Markov models (HMMs) and conduct automatic speech recognition in a conventional way. The results obtained are promising, which confirm that phonetic features characterizing articulation are as discriminating as those characterizing acoustics (except for voicing). The results also show that using tongue parameters result in a higher accuracy compared with the lip parameters. © 2011 IEEE.


Zanlungo F.,Intelligent Robotics and Communication Laboratories | Zanlungo F.,Japan Science and Technology Agency | Ikeda T.,Intelligent Robotics and Communication Laboratories | Ikeda T.,Japan Science and Technology Agency | And 2 more authors.
PLoS ONE | Year: 2012

We propose a way to introduce in microscopic pedestrian models a "social norm" in collision avoiding and overtaking, i.e. the tendency, shared by pedestrians belonging to the same culture, to avoid collisions and perform overtaking in a preferred direction. The "social norm" is implemented, regardless of the specific collision avoiding model, as a rotation in the perceived velocity vector of the opponent at the moment of computation of the collision avoiding strategy, and justified as an expectation that the opponent will follow the same "social norm" (for example a tendency to avoid on the left and overtake on the right, as proposed in this work for Japanese pedestrians). By comparing with real world data, we show that the introduction of this norm allows for a better reproduction of macroscopic pedestrian density and velocity patterns. © 2012 Zanlungo et al.


Ikeda T.,Intelligent Robotics and Communication Laboratories | Chigodo Y.,Intelligent Robotics and Communication Laboratories | Rea D.,Intelligent Robotics and Communication Laboratories | Zanlungo F.,Intelligent Robotics and Communication Laboratories | And 2 more authors.
Robotics: Science and Systems | Year: 2013

This study addresses a method to predict pedestrians' long term behavior in order to enable a robot to provide them services. In order to do that we want to be able to predict their final goal and the trajectory they will follow to reach it. We attain this task borrowing from human science studies the concept of sub-goals, defined as points and landmarks of the environment towards which pedestrians walk or where they take directional choices before reaching the final destination. We retrieve the position of these sub-goals from the analysis of a large set of pedestrian trajectories in a shopping mall, and model their global behavior through transition probabilities between sub-goals. The method allows us to predict the future position of pedestrians on the basis of the observation of their trajectory up to the moment.1 Keywords-component; pedestrian models; sub-goal retrieval; behavior anticipation. © 2013 Massachusetts Institute of Technology.


Lee J.-W.,Korea Advanced Institute of Science and Technology | Lee J.-Y.,Intelligent Robotics and Communication Laboratories | Lee J.-J.,Korea Advanced Institute of Science and Technology
IEEE Wireless Communications Letters | Year: 2013

The Energy-Efficient Coverage (EEC) problem in unstructured Wireless Sensor Networks (WSNs) is an important issue because WSNs have limited energy. In this letter, we propose a novel stochastic optimization algorithm, called the Jenga-Inspired Optimization Algorithm (JOA), which overcomes some of the weaknesses of other optimization algorithms for solving the EEC problem. The JOA was inspired by Jenga which is a well-known board game. We also introduce the probabilistic sensor detection model, which leads to a more realistic approach to solving the EEC problem. Simulation results are conducted to verify the effectiveness of the JOA for solving the EEC problem in comparison with existing algorithms. © 2013 IEEE.


Glas D.F.,Hiroshi Ishiguro Laboratories | Kanda T.,Intelligent Robotics and Communication Laboratories | Ishiguro H.,Osaka University
ACM/IEEE International Conference on Human-Robot Interaction | Year: 2016

Interaction Composer, a visual programming environment designed to enable programmers and non-programmers to collaboratively design social human-robot interactions in the form of state-based flows, has been in use at our laboratory for eight years. The system architecture and the design principles behind the framework have been presented in other work, but in this paper we take a case-study approach, examining several actual examples of the use of this toolkit over an eight-year period. We examine the structure and content of interaction flows, identify common design patterns, and discuss elements of the framework which have proven valuable, features which did not solve their intended purposes, and ways that future systems might better address these issues. It is hoped that the insights gained from this study will contribute to the development of more effective and more usable tools and frameworks for interaction design. © 2016 IEEE.


Zheng K.,Intelligent Robotics and Communication Laboratories | Zheng K.,Osaka University | Glas D.F.,Intelligent Robotics and Communication Laboratories | Glas D.F.,Osaka University | And 4 more authors.
ACM/IEEE International Conference on Human-Robot Interaction | Year: 2013

This paper presents a human study and system implementation for the supervisory control of multiple social robots for navigational tasks. We studied the acceptable range of speed for robots interacting with people through navigation, and we discovered that entertaining people by speaking during navigation can increase people's tolerance toward robots' slow locomotion speed. Based on these results and using a robot safety model developed to ensure safety of robots during navigation, we implemented an algorithm which can proactively adjust robot behaviors during navigation to improve the performance of a human-robot team consisting of a single operator and multiple mobile social robots. Finally, we implemented a semi-autonomous robot system and conducted experiments in a shopping mall to verify the effectiveness of our proposed methods in a real-world environment. © 2013 IEEE.

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