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10th IFAC Symposium on Robot Control, SYROCO 2012

作者： Bohg, Jeannette Welke, Kai León, Beatriz Do, Martin Song, Dan Wohlkinger, Walter Madry, Marianna Aldóma, Aitor Przybylski, Markus Asfour, Tamim Martí, Higinio Kragic, Danica Morales, Antonio Vincze, Markus Humanoids and Intelligence Systems Lab. Institute for Anthropomatics KIT Germany Autonomous Motion Lab. MPI for Intelligent Systems Germany Robotic Intelligence Laboratory Department of Computer Science and Engineering UJI Spain Computer Vision and Active Perception Lab. KTH Sweden Automation and Control Institute TUW Austria

ISBN: (纸本)9783902823113

In this paper, we present an approach towards autonomous grasping of objects according to their category and a given task. Recent advances in the field of object segmentation and categorization as well as task-based grasp inference have been leveraged by integrating them into one pipeline. This allows us to transfer task-specific grasp experience between objects of the same category. The effectiveness of the approach is demonstrated on the humanoid robot ARMAR-IIIa. © 2012 IFAC.

关键词： Anthropomorphic robots

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Machine learning with operational costs

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The Journal of Machine Learning Research 2013年第1期14卷

作者： Kevin Murphy Bernhard Schölkopf Theja Tulabandhula Cynthia Rudin Google MPI for Intelligent Systems Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA MIT Sloan School of Management and Operations Research Center Massachusetts Institute of Technology Cambridge MA

This work proposes a way to align statistical modeling with decision making. We provide a method that propagates the uncertainty in predictive modeling to the uncertainty in operational cost, where operational cost is the amount spent by the practitioner in solving the problem. The method allows us to explore the range of operational costs associated with the set of reasonable statistical models, so as to provide a useful way for practitioners to understand uncertainty. To do this, the operational cost is cast as a regularization term in a learning algorithm's objective function, allowing either an optimistic or pessimistic view of possible costs, depending on the regularization parameter. From another perspective, if we have prior knowledge about the operational cost, for instance that it should be low, this knowledge can help to restrict the hypothesis space, and can help with generalization. We provide a theoretical generalization bound for this scenario. We also show that learning with operational costs is related to robust optimization.

关键词： covering numbers decision theory optimization statistical learning theory

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Bayesian fusion of thermal and visible spectra camera data for region based tracking with rapid background adaptation

Bayesian fusion of thermal and visible spectra camera data f...

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International Conference on Multisensor Fusion and Integration for intelligent systems (MFI)

作者： Rustam Stolkin David Rees Mohammed Talha Ionut Florescu Intelligent Robotics Laboratory of the School of Computer Science University of Binningham UK Department of Mathematical Science Stevens Institute of Technology USA

This paper presents a method for optimally combining pixel information from an infra-red thermal imaging camera, and a conventional visible spectrum colour camera, for tracking a moving target. The tracking algorithm rapidly re-learns its background models for each camera modality from scratch at every frame. This enables, firstly, automatic adjustment of the relative importance of thermal and visible information in decision making, and, secondly, a degree of “camouflage target” tracking by continuously re-weighting the importance of those parts of the target model that are most distinct from the present background at each frame. Furthermore, this very rapid background adaptation ensures robustness to large, sudden and arbitrary camera motion, and thus makes this method a useful tool for robotics, for example visual servoing of a pan-tilt turret mounted on a moving robot vehicle. The method can be used to track any kind of arbitrarily shaped or deforming object, however the combination of thermal and visible information proves particularly useful for enabling robots to track people. The method is also important in that it can be readily extended for data fusion of an arbitrary number of statistically independent features from one or arbitrarily many imaging modalities.

关键词： Target tracking Image color analysis Cameras Robot vision systems Adaptation models Histograms

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An introduction to the special issue: Modeling and control of integrated bio-systems

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WSEAS Transactions on systems 2012年第7期11卷 221-222页

作者： Vassileva, Svetla Neri, Filippo Department of Integrated Systems Institute of Systems Engineering and Robotics Bulgarian Academy of Sciences Sofia Bulgaria Department of Computer Science University of Naples federico II Naples Italy

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Evaluation of fall detection classification approaches

Evaluation of fall detection classification approaches

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International Conference on intelligent and Advanced systems, ICIAS

作者： Hamideh Kerdegari Khairulmizam Samsudin Abdul Rahman Ramli Saeid Mokaram Computer Systems Laboratory Department of Computer and Communication Systems Universiti Putra Malaysia Serdang Malaysia Intelligent Systems and Robotics Laboratory Institute of Advanced Technology Universiti Putra Malaysia Serdang Malaysia

As we grow old, our desire for being independence does not decrease while our health needs to be monitored more frequently. Accidents such as falling can be a serious problem for the elderly. An accurate automatic fall detection system can help elderly people be safe in every situation. In this paper a waist worn fall detection system has been proposed. A tri-axial accelerometer (ADXL345) was used to capture the movement signals of human body and detect events such as walking and falling to a reasonable degree of accuracy. A set of laboratory-based falls and activities of daily living (ADL) were performed by healthy volunteers with different physical characteristics. This paper presents the comparison of different machine learning classification algorithms using Waikato Environment for Knowledge Analysis (WEKA) platform for classifying falling patterns from ADL patterns. The aim of this paper is to investigate the performance of different classification algorithms for a set of recorded acceleration data. The algorithms are Multilayer Perceptron, Naive Bayes, Decision tree, Support Vector Machine, ZeroR and OneR. The acceleration data with a total data of 6962 instances and 29 attributes were used to evaluate the performance of the different classification algorithm. Results show that the Multilayer Perceptron algorithm is the best option among other mentioned algorithms, due to its high accuracy in fall detection.

关键词： Acceleration Feature extraction Accuracy Support vector machines Senior citizens Accelerometers Classification algorithms

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Mobile robots communication and control framework for USARSim

Mobile robots communication and control framework for USARSi...

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International Conference on intelligent and Advanced systems, ICIAS

作者： Saeid Mokaram Khairulmizam Samsudin Abdul Rahman Ramli Hamideh Kerdegari Computer Systems Laboratory Department of Computer and Communication Systems Universiti Putra Malaysia Serdang Malaysia Intelligent Systems and Robotics Laboratory Institute of Advanced Technology Universiti Putra Malaysia Serdang Malaysia

In recent years there have been intensive efforts in robotics researches from the earliest stages of education. Subject of this paper is a powerful mobile robot communication and control framework for USARSim simulator that can be used both for research and education. Mobile Robots Communication and Control Framework (MCCF) is developed in order to offer faster and easier communication process with the USARSim server within Matlab that differentiates it from most existing basic open source control interfaces. Most notably, it takes the advantages of easy integration with other analysis and control methods that have been provided in Matlab tool-boxes. MCCF enables communication and control of a wide range of robots platforms including but not limited to wheeled-robots, legged-robots, submarine robots and aerial robots. In this paper we describe its general architecture, features and examples of utilization for researchers who are interested in mobile robot simulations for education and research.

关键词： Robot sensing systems MATLAB Mobile robots Servers Java

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Conversational gaze mechanisms for humanlike robots

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ACM Transactions on Interactive intelligent systems 2012年第2期1卷 1–33页

作者： Mutlu, Bilge Kanda, Takayuki Forlizzi, Jodi Hodgins, Jessica Ishiguro, Hiroshi Department of Computer Sciences University of Wisconsin-Madison 1210W. Dayton St. Madison WI 53706 United States Intelligent Robotics and Communication Laboratories ATR 2-2-2 Hikaridai Soraku-gun Seika-cho Kyoto 619-0224 Japan Human-Computer Interaction Institute Carnegie Mellon University 5000 Forbes Ave. Pittsburgh PA 15213 United States Robotics Institute Carnegie Mellon University 5000 Forbes Ave. Pittsburgh PA 15213 United States Department of System Innovation Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka Japan

During conversations, speakers employ a number of verbal and nonverbal mechanisms to establish who participates in the conversation, when, and in what capacity. Gaze cues and mechanisms are particularly instrumental in establishing the participant roles of interlocutors, managing speaker turns, and signaling discourse structure. If humanlike robots are to have fluent conversations with people, they will need to use these gaze mechanisms effectively. The current work investigates people's use of key conversational gaze mechanisms, how they might be designed for and implemented in humanlike robots, and whether these signals effectively shape human-robot conversations. We focus particularly on whether humanlike gaze mechanisms might help robots signal different participant roles, manage turn-exchanges, and shape how interlocutors perceive the robot and the conversation. The evaluation of these mechanisms involved 36 trials of three-party human-robot conversations. In these trials, the robot used gaze mechanisms to signal to its conversational partners their roles either of two addressees, an addressee and a bystander, or an addressee and a nonparticipant. Results showed that participants conformed to these intended roles 97% of the time. Their conversational roles affected their rapport with the robot, feelings of groupness with their conversational partners, and attention to the task. © 2012 ACM.

关键词： Human robot interaction

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Self-system in a model of cognition

Self-system in a model of cognition

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作者： Ramamurthy, Uma Franklin, Stan Agrawal, Pulin Department of Pediatrics Dan L. Duncan Institute for Clinical and Translational Research Baylor College of Medicine One Baylor Plaza Houston TX 77030 United States Department of Computer Science Institute for Intelligent Systems University of Memphis Memphis TN 38152 United States

Philosophers, psychologists and neuroscientists have proposed various forms of a «self» in humans and animals. All of these selves seem to have a basis in some form of consciousness. The Global Workspace Theory (GWT) [Baars, 1988, 2003] suggests a mostly unconscious, many-layered self-system. In this paper, we consider several issues that arise from attempts to include a self-system in a software agent/cognitive robot. We explore these issues in the context of the LIDA model [Baars and Franklin, 2009;Ramamurthy et al., 2006] which implements the Global Workspace Theory. © 2012 World Scientific Publishing Company.

关键词： Software agents

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Maximum volume clustering: a new discriminative clustering approach

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The Journal of Machine Learning Research 2013年第1期14卷

作者： Kevin Murphy Bernhard Schölkopf Gang Niu Bo Dai Lin Shang Masashi Sugiyama Google MPI for Intelligent Systems Department of Computer Science Tokyo Institute of Technology Tokyo Japan College of Computing Georgia Institute of Technology Atlanta GA State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

The large volume principle proposed by Vladimir Vapnik, which advocates that hypotheses lying in an equivalence class with a larger volume are more preferable, is a useful alternative to the large margin principle. In this paper, we introduce a new discriminative clustering model based on the large volume principle called maximum volume clustering (MVC), and then propose two approximation schemes to solve this MVC model: A soft-label MVC method using sequential quadratic programming and a hard-label MVC method using semi-definite programming, respectively. The proposed MVC is theoretically advantageous for three reasons. The optimization involved in hard-label MVC is convex, and under mild conditions, the optimization involved in soft-label MVC is akin to a convex one in terms of the resulting clusters. Secondly, the soft-label MVC method possesses a clustering error bound. Thirdly, MVC includes the optimization problems of a spectral clustering, two relaxed k-means clustering and an information-maximization clustering as special limit cases when its regularization parameter goes to infinity. Experiments on several artificial and benchmark data sets demonstrate that the proposed MVC compares favorably with state-of-the-art clustering methods.

关键词： clustering error bound discriminative clustering finite sample stability large volume principle semi-definite programming sequential quadratic programming

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Bayesian fusion of thermal and visible spectra camera data for mean shift tracking with rapid background adaptation

Bayesian fusion of thermal and visible spectra camera data f...

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IEEE Sensors Conference

作者： Rustam Stolkin David Rees Mohammed Talha Ionut Florescu Intelligent Robotics Lab School of Computer Science University of Birmingham UK Department of Mathematical Sciences Stevens Institute of Technology USA

ISBN: (纸本)9781457717666

This paper presents a method for optimally combining pixel information from thermal imaging and visible spectrum colour cameras, for tracking an arbitrarily shaped deformable moving target. The tracking algorithm rapidly relearns its background models for each camera modality from scratch at every frame. This enables, firstly, automatic adjustment of the relative importance of thermal and visible information in decision making, and, secondly, a degree of "camouflage target" tracking by continuously re-weighting the importance of those parts of the target model that are most distinct from the present background at each frame. Furthermore, this very rapid background adaptation ensures robustness to rapid camera motion. The combination of thermal and visible information is applicable to any target, but particularly useful for people tracking. The method is also important in that it can be readily extended for fusion of data from arbitrarily many imaging modalities.

关键词： Target tracking Image color analysis Cameras Mathematical model Equations Histograms

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