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IEEE-RAS International Conference on Humanoid Robots

作者： Serena Ivaldi Jan Peters Vincent Padois Francesco Nori TU Darmstadt The Intelligent Autonomous Systems Lab Germany The Max Planck Institute for Intelligent Systems CNRS Sorbonne Universités France The Robotics Italian Institute of Technology

ISBN: (纸本)9781479971756

The number of tools for dynamics simulation has grown substantially in the last few years. Humanoid robots, in particular, make extensive use of such tools for a variety of applications, from simulating contacts to planning complex motions. It is necessary for the humanoid robotics community to have a systematic evaluation to assist in choosing which of the available tools is best for their research. This paper surveys the state of the art in dynamics simulation and reports on the analysis of an online survey about the use of dynamics simulation in the robotics research community. The major requirements for robotics researchers are better physics engines and open-source software. Despite the numerous tools, there is not a general-purpose simulator which dominates the others in terms of performance or application. However, for humanoid robotics, Gazebo emerges as the best choice among the open-source projects, while V-Rep is the preferred commercial simulator. The survey report has been instrumental for choosing Gazebo as the base for the new simulator for the iCub humanoid robot.

关键词： Robots Physics Engines Open source software Communities Collision avoidance

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On human performance in tactile language learning and tactile memory

On human performance in tactile language learning and tactil...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Ramiro Velázquez Edwige Pissaloux Mechatronics and Control Systems Lab. (MCS) Universidad Panamericana Aguascalientes Mexico Institute for Intelligent Systems and Robotics (ISIR) Paris France

This paper reports on the findings from an experiment on human performance in tactile language learning and tactile memory. A set of vibrotactile patterns representing verbal words was presented to a group of 20 voluntary subjects. Upon learning, subjects were capable of recognizing the patterns with high accuracy. Patterns were then combined with the aim of constructing sentences that gradually represent more complex ideas. Recognition rates remained satisfactory. A novel approach of tactile stimuli was explored: podotactile stimulation. For this study, a prototype of wearable electronic tactile display that stimulates the mechanoreceptors in the foot sole with vibrations was used. Results obtained suggest that it is possible to construct tactile languages that could be useful in human-computer interaction and wearable/mobile computing.

关键词： Foot Prototypes Vibrations Robot sensing systems Human computer interaction Vocabulary

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A vision-based automatic hotline tracking approach using unscented Kalman filter

A vision-based automatic hotline tracking approach using uns...

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Sepehr Valipour Hadi Moradi Advanced Robotics and Intelligent Systems lab University of Tehran Tehran Iran CIPC University of Tehran Tehran Iran

Hotline inspection is a necessary, dangerous, and in many cases a very hard task. In this paper we present a vision-based approach, suitable for aerial inspection system, that automatically tracks a desired hotline to ease up the operation and would let the operator to focus on inspection of the lines. The operator flies the aerial inspection system and places it in the vicinity of a hotline. The aerial flying vehicle is equipped with a camera that is used to capture images of the desired hotline and finds the hotline in the image. Then the tracking system uses an Unscented Kalman Filter (UKF) to handle the disturbances that happens while the aerial system flies across the lines. The system has been simulated and actually tested which shows its capability to successfully and reliably follow hotlines.

关键词： Cameras Feature extraction Inspection Vehicles Reliability Image edge detection Helicopters

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Learning interaction for collaborative tasks with probabilistic movement primitives

Learning interaction for collaborative tasks with probabilis...

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IEEE-RAS International Conference on Humanoid Robots

作者： Guilherme Maeda Marco Ewerton Rudolf Lioutikov Heni Ben Amor Jan Peters Gerhard Neumann Intelligent Autonomous Systems Lab Technische Universitaet Darm-stadt Darmstadt Germany Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA USA Max Planck Institute for Intelligent Systems Tuebingen Germany

This paper proposes a probabilistic framework based on movement primitives for robots that work in collaboration with a human coworker. Since the human coworker can execute a variety of unforeseen tasks a requirement of our system is that the robot assistant must be able to adapt and learn new skills on-demand, without the need of an expert programmer. Thus, this paper leverages on the framework of imitation learning and its application to human-robot interaction using the concept of Interaction Primitives (IPs). We introduce the use of Probabilistic Movement Primitives (ProMPs) to devise an interaction method that both recognizes the action of a human and generates the appropriate movement primitive of the robot assistant. We evaluate our method on experiments using a lightweight arm interacting with a human partner and also using motion capture trajectories of two humans assembling a box. The advantages of ProMPs in relation to the original formulation for interaction are exposed and compared.

关键词： Trajectory Robot kinematics Hidden Markov models Collaboration Vectors Probabilistic logic

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Classification of left/right hand movement from EEG signal by intelligent algorithms

Classification of left/right hand movement from EEG signal b...

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International Conference on Computer Applications and Industrial Electronics (ICCAIE)

作者： Muhammad Zeeshan Baig Ehtasham Javed Yasar Ayaz Waseem Afzal Syed Omer Gillani Muhammad Naveed Mohsin Jamil Department of Robotics and Artificial Intelligence Robotics and Intelligent Systems Engineering (RISE) Lab Islamabad Pakistan Centre for Intelligent Signal and Imaging Research (CISIR) Universiti Teknologi PETRONAS Malaysia Department of Electronic Engineering Mohammad Ali Jinnah University Islamabad Pakistan

Brain Computer interface (BCI) shown enormous ability to advance the human way of life. Furthermore its application is also targeting the disabled ones. In this research, we have implemented a new approach to classify EEG signals more efficiently. The dataset used for this purpose is from BCI competition-II 2003 named Graz database. Initial processing of the EEG signals has been carried out on 2 electrodes named C3 & C4; after that the bi-orthogonal wavelet coefficients, Welench Power Spectral Density estimates and the average power were used as a feature set for classification. We have given a relative study of currently used classification algorithms along with a new approach for classification i.e. Self-organizing maps (SOM) based neural network technique. It is used to classify the feature vector obtain from the EEG dataset, into their corresponding classes belong to left/right hand movements. Algorithms have been implemented on both unprocessed features and processed reduced feature sets. Principal component Analysis (PCA) has been used for feature reduction. Measured data revealed that the maximum classification accuracy of 84.17% on PCA implemented reduce feature set has been achieved using SOM based classifier. Furthermore, the classification accuracy has been increased about 2% by simply using bi-orthogonal Wavelet transform rather than Daubechies wavelet transform.

关键词： Feature extraction Electroencephalography Wavelet transforms Classification algorithms Support vector machine classification Electrodes

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Determining mood via emotions observed in face by induction

Determining mood via emotions observed in face by induction

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RSI/ISM International Conference on robotics and Mechatronics (ICROM)

作者： Mojgan Hashemian Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

Determining the mood of a person is an important step in the Human-Robot interaction. In this paper, we propose a human-inspired approach in which the changes in emotions, done using emotion induction, can be used to determine the mood of a person. The emotion induction, which can be done through robot actions or through showing video clips, stimulates changes in the emotions of the person, reducing the observation time needed to estimate mood. Consequently, the changes in the emotions, which are biased by his/her mood can be used by a robot to determine the mood of a person. To do so, we induced happy emotions by showing a comical clip and measured the intensity of each happy and sad emotions, and also the intensity of the neutral state. Then we extracted a feature set, including both time and frequency domain features, which is used to determine the mood of the person. The approach has been implemented and compared to no-emotion-induction approach and shows better results. Based on the classification results, the approach is able to distinguish between good vs. bad moods with the accuracy of 91.5% with 0.1 mean absolute error. But the neutral state was not distinguishable well.

关键词： Mood Robots Accuracy Feature extraction Face Educational institutions Human-robot interaction

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Opening remarks

2016 International Conference on Advances in Human Machine I...

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2016 International Conference on Advances in Human Machine Interaction, HMI 2016 2016年

作者： Nagaraja, Ch. Swamy, J. Nagendra Rajendra, J. Khan, M.S. Vishwanath Reddy, D.S. Manjunath, N. Dillmann, Ruediger Tarn, Tzyh Jong Zhao, Qianchuan Ammi, Mehdi Zuberek, Wlodek M. Sandhu, P.S. Patthira Newman, K. De Silva Liyanage, Chandratilak Hassan, Sohair Aly Aly Sun, Kien Wen Rahman, Md. Moshiur Ordoño, E. Evangelista Sharma, R.K. Mishra, Preeti Chandel, B.S. Singla, Ekta Petric, Tadej Zhong, Yu Jiglar, Janson Alemzadeh, Kazem Asokan, T. Tripathi, Animesh Tripathi, Manoj Ram, Swaminath Shrma, M.K. Panday, P.N. Kumar, Devendra Hinchey, Mike Stilman, Boris Suraj, Zbigniew Pal, Sankar K. Sasi, Sreela Rajan, Deepu Marshall, Roger G. Abraham, Ajith Peter S, David Paul, Vargheese Gopakumar, V. Dustdar, Schahram Soto, Sebastián Ventura Rausch, Andreas Angelis, Lefteris Nelson, Andrew L. Botzheim, Janos Bernardino, Heder Soares Zboril, Frantisek Ane, Bernadetta Kwintiana Maeda, Toshiyuki Sakalauskas, Virgilijus Hann, Garenth Lim King Samek, Jan Romero Salguero, José Raúl Varghese, Kuruvilla Kriksciuniene, Dalia Mathew, Jimson Reif, Wolfgang Mauri, Giancarlo Cabrerizo Lorite, Francisco Javier Özcan, Ender Cho, Sung-Bae Paily, Roy P. Rezankova, Hana Tudjarov, Boris Hong, Wei-Chiang De Oliveira, José Valente Flores Romero, Juan Jose Oskouei, Rozita Jamili Cicchetti, Antonio Roy, Chanchal Segura, Sergio Samuel, C. Mallet, Frédéric Mernik, Marjan Punnekkat, Sasikumar Waseemulla, A. Sri Devaraj Urs Educational Trust Bangalore India R. L. Jalappa Institute of Technology Doddaballapur Bangalore India Humanoids and Intelligence Systems Lab Kalsruhe Germany Electrical and Systems Engineering Washington University in St. Louis United States Deputy Director of Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing China Department of Computer Science CNRS/LIMSI Lab AMI Group France Memorial University St. John'sNL Canada RBIT and Bio-Technology India LR University Thailand University of Colorado at Boulder Boulder United States Faculty of Science University of Brunei Brunei University of Kuala Lumpur Malaysia National Chiao Tung University Taiwan EPR Centre Bangladesh Mapua Institute of Technology Philippines ARO CWC Lucknow India Mpec Kanpur India DSC DBS Kanpu India Indian Institute of Technology Ropar India Jozaf Stefan Institute Department of Automation Biocyernetics and Robotics Ljubljana Slovenia Robotics Institute Carnegie Mellon University Pittsburgh United States Faculty of Engineering University of Bristol United Kingdom Department of Engineering Design Indian Institute of Technology Madras India Lucknow Uni Lucknow India CSJM Uni Kanpur India UPPCB Lucknow India PCB Roorkee India Awadh Uni Faijabad India Agra Uni Agra India Lero University of Limerick Ireland University of Colorado Denver United States University of Rzeszow Poland Indian Statistical Institute Kolkata India Gannon University PA United States Nanyang Technical University Singapore Singapore Plymouth State University NH United States MIR Labs United States Cochin University of Science and Technology India State Project Facilitation Unit TEQIP Kerala India Technical University of Vienna Austria University of Cordoba Spain Clausthal University of Technology Germany Aristotle University of Thessaloniki Greece Androtics LLC TucsonAZ United States Tokyo Metropolitan University Japan Federal Unive

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Combining Top-down Spatial Reasoning and Bottom-up Object Class Recognition for Scene Understanding

Combining Top-down Spatial Reasoning and Bottom-up Object Cl...

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Lars Kunze Chris Burbridge Marina Alberti Akshaya Tippur John Folkesson Patric Jensfelt Nick Hawes Intelligent Robotics Lab School of Computer Science University of Birmingham United Kingdom Centre for Autonomous Systems KTH Royal Institute of Technology SE-100 44 Stockholm Sweden

ISBN: (纸本)9781479969357

Many robot perception systems are built to only consider intrinsic object features to recognise the class of an object. By integrating both top-down spatial relational reasoning and bottom-up object class recognition the overall performance of a perception system can be improved. In this paper we present a unified framework that combines a 3D object class recognition system with learned, spatial models of object relations. In robot experiments we show that our combined approach improves the classification results on real world office desks compared to pure bottom-up perception. Hence, by using spatial knowledge during object class recognition perception becomes more efficient and robust and robots can understand scenes more effectively.

关键词： object class Object Relations Robot bottom-up spatial reasoning senses Perception top-down

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Determining mood using emotional features

Determining mood using emotional features

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International Symposium on Telecommunications, IST

作者： Mojgan Hashemian Amin Nikoukaran Hadi Moradi Maryam S Mirian Mehdi Tehrani-doost Advanced Robotics and Intelligent Systems Lab University of Tehran Iran School of Electrical and Computer Engineering University of Tehran Iran Department of Psychiatry Tehran University of Medical Science Iran

The ability to determine mood is one of fundamental challenges in affective computing. In this paper, we present a novel approach for mood detection via emotional variations. In this approach, the mood is considered as a low magnitude and more stable, i.e. low frequency, emotion that can be detected using emotion detection approaches. A Bayes classification is applied on a feature vector composed of statistical aspects of the intensity of the emotions. The approach has been implemented in which two emotions, i.e. happiness and sadness, and also neutral state, have been targeted to determine the good, bad, and neutral, mood of subjects respectively. A Bayes classification is applied on a feature vector containing statistical aspects of the intensity of the emotions. The obtained Correct Classification Rate (CCR) is 91.1, with 0.09 mean error and variance of 4.9 discriminating good mood vs. neutral.

关键词： Mood Educational institutions Face Videos Computers Mice Accuracy

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Kinematics Modeling and Experimental Verification of Baxter Robot

Kinematics Modeling and Experimental Verification of Baxter ...

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第三十三届中国控制会议

作者： Zhangfeng JU Chenguang YANG Hongbin MA North Automatic Control Technology Institute Centre for Robotics and Neural Systems School of Computing and MathematicsPlymouth University School of Automation Beijing Institute of Technology StateKey Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781479947249

The Baxter R humanoid robot made by Rethink roboticsTMoffers users an affordable platform with guaranteed safety for both academic and industrial *** platform provides the users a good opportunity to carry out research on dualarm robot manipulation and vision based *** simulation of the Baxter R robot,a proper kinematic and dynamic model should be *** Baxter robot uses URDF file to describe the robot kinematics,i.e.,the relationship between adjacent joint and *** the large difference between the structure of URDF and the conventional Denavit-Hartenburg(DH) notations which are widely used in robotics literature,we perform rigorous theoretic analysis of kinematics of Baxter R robot including all limbs.A kinematics model has been built following DH convention,and has been implemented in the MATlab robotics *** comparison between simulation and experimental results has verified the validity of the kinematic model.

关键词： Baxter R robot,Simulink model,DH convention

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