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International Conference on Information and Automation (ICIA)

作者： Yuanrong Xu Qianqian Wang Xiao Bai Yen-Lun Chen Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences University of Science and Technology of China Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

In this paper, we propose a method based on the SVM algorithm to recognize dynamic hand gestures. The information of motion trajectory is captured by a leap motion in three-dimension space. A new methodology of feature extracting is proposed to guarantee the length of samples being the same. The elements of feature vectors are ranged according to two different criteria: one is the amplitude of the variation of orientation angles, and the other criterion is the order of the appearance of features. Experimental results show that this method can classify the dynamic hand gestures effectively.

关键词： Vectors Trajectory Feature extraction Equations Mathematical model Hidden Markov models Automation

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Teachers' views on the use of empathic robotic tutors in the classroom

Teachers' views on the use of empathic robotic tutors in the...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Sofia Serholt Wolmet Barendregt Iolanda Leite Helen Hastie Aidan Jones Ana Paiva Asimina Vasalou Ginevra Castellano Department of Applied Information Technology University of Gothenburg Gothenburg Sweden GAIPS Instituto Superior Tecnico Lisboa Portugal Social Robotics Lab Yale University New Haven CT USA School of Mathematical and Computer Science Heriot-Watt University Edinburgh UK School of Electronic Electrical and Computer Engineering University of Birmingham Birmingham UK London Knowledge Lab Institute of Education London UK

ISBN: (纸本)9781479967667

In this paper, we describe the results of an interview study conducted across several European countries on teachers' views on the use of empathic robotic tutors in the classroom. The main goals of the study were to elicit teachers' thoughts on the integration of the robotic tutors in the daily school practice, understanding the main roles that these robots could play and gather teachers' main concerns about this type of technology. Teachers' concerns were much related to the fairness of access to the technology, robustness of the robot in students' hands and disruption of other classroom activities. They saw a role for the tutor in acting as an engaging tool for all, preferably in groups, and gathering information about students' learning progress without taking over the teachers' responsibility for the actual assessment. The implications of these results are discussed in relation to teacher acceptance of ubiquitous technologies in general and robots in particular.

关键词： Educational institutions Interviews Robot sensing systems Service robots Europe

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Dynamic hand gesture early recognition based on Hidden Semi-Markov Models

Dynamic hand gesture early recognition based on Hidden Semi-...

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IEEE International Conference on robotics and Biomimetics

作者： Qianqian Wang Yuanrong Xu Yen-Lun Chen Yong Wang Xinyu Wu University of Science and Technology of China Shenzhen Key Lab for Computer Vision and Pattern Recognition Chinese Academy of Sciences Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong. Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences

ISBN: (纸本)9781479973989

Real-time performance can be greatly improved, if the early recognition is implemented. In this paper, a dynamic hand gesture early recognition system is proposed. The system can recognize the gesture before it is completed. Our method is based on the Hidden Semi-Markov Models. Three-dimensional information of the gesture trajectory collected by leapmotion is the main data we used. Experiments on the dataset which we established demonstrate the effectiveness of our method.

关键词： Hidden Markov models Gesture recognition Training Conferences Trajectory Arrays

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Area coverage planning that accounts for pose uncertainty with an AUV seabed surveying application

Area coverage planning that accounts for pose uncertainty wi...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Liam Paull Mae Seto Howard Li Computer Science and AI Lab Massachusetts Institute of Technology Cambridge Massachusetts USA Mine and Harbour Defense Group Defense R&D Canada Dartmouth Nova Scotia Canada Collaborative Based Robotics and Automation (COBRA) group University of New Brunswick Fredericton New Brunswick Canada

This paper presents an overview of our research on accounting for robot pose uncertainty in area coverage applications. In the vast majority of existing literature on robotics area coverage, the location uncertainty of the robot is not considered. An uncertain robot pose results in an uncertain sensor swath, which in turn creates uncertainty about the achieved coverage. Here, we present a general framework where pose estimates are mapped through the coverage sensor model to obtain a probability of coverage over the discretized workspace. This probabilistic representation can then be used to adaptively plan paths for coverage based on an entropy reduction formulation. This framework is particularly well-suited to autonomous underwater vehicles (AUVs) performing seabed surveying operations. The AUV position estimate diverges from the actual AUV position while submerged due to the lack of a global position reference. This discrepancy can result in parts of the seabed being missed, which is unacceptable in safety-critical missions such as mine countermeasures. The proposed information-based path planning approach is able to guarantee area coverage even in the case of severe AUV position estimate drift. In-water experiments with an AUV show the effectiveness of the method.

关键词： Robot sensing systems Uncertainty Probabilistic logic Sonar Vehicles Global Positioning System

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Automated classification of therapeutic face exercises using the kinect

Automated classification of therapeutic face exercises using...

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8th International Conference on computer Vision Theory and Applications, VISAPP 2013

作者： Lanz, Cornelia Olgay, Birant Sibel Denzler, Joachim Gross, Horst-Michael Neuroinformatics and Cognitive Robotics Lab Ilmenau University of Technology Ilmenau Germany Computer Vision Group Friedrich Schiller University Jena Jena Germany

ISBN: (纸本)9789898565471

In this work, we propose an approach for the unexplored topic of therapeutic facial exercise recognition using depth images. In cooperation with speech therapists, we determined nine exercises that are beneficial for therapy of patients suffering from dysfunction of facial movements. Our approach employs 2.5D images and 3D point clouds, which were recorded using Microsoft's Kinect. Extracted features comprise the curvature of the face surface and characteristic profiles that are derived using distinctive landmarks. We evaluate the discriminative power and the robustness of the features with respect to the above-mentioned application scenario. Using manually located face regions for feature extraction, we achieve an average recognition accuracy of about 91% for the nine facial exercises. However in a real-world scenario manual localization of regions for feature extraction is not feasible. Therefore, we additionally examine the robustness of the features and show, that they are beneficial for a real-world, fully automated scenario as well.

关键词： Feature extraction

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ARTIFICIAL ENDOCRINE SYSTEM: A NEW PARADIGM OF KNOWLEDGE DISCOVERY

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International Journal of Information Acquisition 2014年第3N04期9卷

作者： SUBHASH CHANDRA PANDEY GORA CHAND NANDI Computer Science and Engineering Department Birla Institute of Technology Mesra Ranchi (Allahabad Campus) Allahabad UP India Artificial Intelligence and Robotics Lab Indian Institute of Information Technology Allahabad UP India

We propose an artificial endocrine system (AES) for extracting the knowledge from database so that effective and reliable decision rules can be constructed. The proposed AES mimics the functionality of biological endocrine system (BES) to some extent. A mathematical model is proposed for expressive representation of endocrine system as well as for homeostasis. Further, different aspects of our proposed "Artificial endocrine system for knowledge discovery" (AESKD) have been compared with state of art classifiers e.g., support vector machine, neural network, radial basis function (RBF) network and K-NN for some bench mark datasets.

关键词： Bio-inspired computation knowledge discovery data mining artificial endocrine system homeostasis

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Adaptive Neural Network Control for a Robotic Manipulator with Unknown Deadzone

Adaptive Neural Network Control for a Robotic Manipulator wi...

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第三十二届中国控制会议

作者： Shuzhi Sam Ge Wei He Shengtao Xiao Robotics Institute and School of Computer Science and Engineering University of Electronic Science and Technology of China Department of Electrical & Computer Engineering National University of Singapore Social Robotics Lab Interactive Digital Media InstituteNational University of Singapore Robotics Institute and School of Automation Engineering University of Electronic Science and Technology of China

ISBN: (纸本)9781479900305

In this paper,adaptive neural network control is designed for a robotic manipulator with unknown *** networks are used to compensate for the unknown deadzone effect faced by the manipulator's ***-feedback control is proposed first and high-gain observer is then designed to make the proposed control scheme more *** deadzone effect is approximated by a Radial Basis Function Neural Network(RBFNN) and the tracking error for the deadzone effect is bounded and *** unknown dynamics of the robotic manipulator is estimated with another *** for the estimated deadzone effect in the control law then leads to our proposed *** proposed control is then verified on a two-joint rigid manipulator via numerical simulations.

关键词： Neural network control Unknown deadzone Radial basis function neural network(RBFNN) Robotic manipulator.

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Vision guided path planning system for vehicles using infrared landmark

Vision guided path planning system for vehicles using infrar...

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IEEE International Conference on robotics and Biomimetics

作者： Malik Saad Sultan Xiaopeng Chen Nouman Qadeer Tongtong Zhang Huang Qiang Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing China Lab of Intelligent Information and Technology School of Computer Science and Technology Beijing Institute of Technology Beijing China

Infrared-landmark based vision navigation system is proposed to reliably guide drivers from starting point to goal following a feasible shortest path in a known indoor or outdoor environment no matter whether it is day or night. What's more, this system is capable of warning drivers about the dangerous zones “like no right turn, no U-turn, damaged road ahead etc” conditions when no visible light is available for human beings, mostly at night. The system consists of Basler camera, designed Infra-Red landmark, our developed software, IR filter and an industrial computer. Each infrared landmark contains a unique ID. Address information and important notes are attached to each ID. Once a landmark is efficiently detected and its ID is recognized, location information related to the corresponding ID is presented. And then Dijkstra's algorithm is efficiently utilized to find a possible shortest path to destination. After that, path is followed with the aid of vision system. Experimental results demonstrate suitability, effectiveness and feasibility in intelligent transportation system.

关键词： Cameras Vehicles Reliability Algorithm design and analysis Optical filters Machine vision Filtering algorithms

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Caging Complex Objects with Geodesic Balls

Caging Complex Objects with Geodesic Balls

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Dmitry Zarubin Florian T. Pokorny Marc Toussaint Danica Kragic Machine Learning and Robotics Lab Universitat Stuttgart Stuttgart Germany Centre for Autonomous Systems Computer Vision and Active Perception Lab School of Computer Science and Communication KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781467363563

This paper proposes a novel approach for the synthesis of grasps of objects whose geometry can be observed only in the presence of noise. We focus in particular on the problem of generating caging grasps with a realistic robot hand simulation and show that our method can generate such grasps even on complex objects. We introduce the idea of using geodesic balls on the object's surface in order to approximate the maximal contact surface between a robotic hand and an object. We define two types of heuristics which extract information from approximate geodesic balls in order to identify areas on an object that can likely be used to generate a caging grasp. Our heuristics are based on two scoring functions. The first uses winding angles measuring how much a geodesic ball on the surface winds around a dominant axis, while the second explores using the total discrete Gaussian curvature of a geodesic ball to rank potential caging postures. We evaluate our approach with respect to variations in hand kinematics, for a selection of complex real-world objects and with respect to its robustness to noise.

关键词： Caging Complex Objects Geodesic Balls Gaussian curvature

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ONLINE ADAPTIVE DICTIONARY LEARNING AND WEIGHTED SPARSE CODING FOR ABNORMALITY DETECTION

ONLINE ADAPTIVE DICTIONARY LEARNING AND WEIGHTED SPARSE CODI...

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IEEE International Conference on Image Processing

作者： Sheng Han Ruiqing Fu Suzhen Wang Xinyu Wu Shenzhen Key Lab for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong

ISBN: (纸本)9781479923427

This paper focuses mainly on adaptive dictionary updating and abnormality detection via weighted space coding in video surveillance. Generally, abnormality analysis conducted on a large amount of video data is very complicated, time-consuming and time-variant. However, our dictionary is very efficient at following up on shifted contents in video and abandoning old inactive information in time. The adaptability characteristic also helps reduce the dictionary's size to a small scale, since it only needs to keep recent or active information. We also introduce a simple, but effective, judgement criterion for abnormal detection based on sparse coding over weighted bases. Because of the condensed dictionary and the simplified judgment criterion, our algorithm performs online learning and online detection with a high speed and a high accuracy in various scenes.

关键词： Dictionary Learning Adaptive Learning Sparse Coding Abnormality Detection Sparse coding anomaly detection video data Dictionaries as Topic video monitoring

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