Conferences related to Robots

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ICASSP 2017 - 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.

  • ICASSP 2015 - 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

    The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.

  • ICASSP 2014 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

    ICASSP 2014 will be the world s largest and most comprehensive technical conference focused on the many facets of signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and oral/poster sessions on the most up-to-date topics in signal processing research.

  • ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

    The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.

  • ICASSP 2012 - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing

    The latest research results on both theories and applications on signal processing will be presented and discussed among participants from all over the world. Video/Speech Signal processing used in human interface between Robots and Personal users will be highlighted.


2014 5th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

Theoretical and experimental challenges posed by the application of robotics and mechatronics in medicine and biology. Analysis of biological systems from a biomechatronic point of view. Design and fabrication of bio-inspired and biomimetic machines. Robotic and mechatronic devices and systems for prevention, diagnosis, surgery, prosthetics, rehabilitation and personal assistance.

  • 2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2012)

    Theoretical and experimental challenges posed by the application of robotics and mechatronics in medicine and biology. Analysis of biological systems from biomechatronic point of view. Design and fabrication of bio-inspired machines. Robotic and mechatronic devices and systems for prevention, diagnosis, surgery, prosthetics, rehabilitation and personal assistance.

  • 2010 3rd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2010)

    Theoretical and experimental challenges posed by the application of robotics and mechatronics in medicine and biology. Analysis of biological systems from a biomechatronic point of view. Design and fabrication of bio-inspired machines and systems for diagnosis, surgery, prosthetics, rehabilitation and personal assistance.

  • 2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2008)

    The main focus of Biorobotics is to analyze biological systems from a "biomechatronic" point of view, trying to understand the scientific and engineering principles underlying their extraordinary performance. This profound understanding of how biological systems work, behave and interact can be used for two main objectives: to guide the design and fabrication of novel, high performance bio-inspired machines and systems, for many different potential applications; and to develop (nano, micro, macro) novel dev

  • 2006 1st IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob 2006)


2014 IEEE International Conference on Robotics and Automation (ICRA)

Robotics and Automation


2014 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014)

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2013 13th IEEE-RAS International Conference on Humanoid Robots (Humanoids 2013)

Humanoids in the Real World: All related areas of humanoid robotics including locomotion, architectures, mechatronics, control, perception, planning, learning, neuroscience and interaction.


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Periodicals related to Robots

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Intelligent Systems, IEEE

IEEE Intelligent Systems, a bimonthly publication of the IEEE Computer Society, provides peer-reviewed, cutting-edge articles on the theory and applications of systems that perceive, reason, learn, and act intelligently. The editorial staff collaborates with authors to produce technically accurate, timely, useful, and readable articles as part of a consistent and consistently valuable editorial product. The magazine serves software engineers, systems ...


Proceedings of the IEEE

The most highly-cited general interest journal in electrical engineering and computer science, the Proceedings is the best way to stay informed on an exemplary range of topics. This journal also holds the distinction of having the longest useful archival life of any EE or computer related journal in the world! Since 1913, the Proceedings of the IEEE has been the ...


Robotics, IEEE Transactions on

Publishes fundamental papers on all aspects of Robotics, featuring interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and other fields. Robots and intelligent machines and systems are critical in areas such as industrial applications; service and personal assistants; surgical operations; space, underwater, and remote exploration; entertainment; safety, search, and rescue; military applications; agriculture applications; and intelligent ...




Xplore Articles related to Robots

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A partition method for UAV's envelope based on fuzzy clustering

Zhao Saifeng; Li Xiujuan; Li Chuntao 2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC), 2016

In this paper, a partition method for envelope based on fuzzy clustering is designed to obtain the typical operating points as well as the interpolation mechanism of gain scheduling according to the comparability of the dynamic characteristics and the maneuverability in some partial flight regions. In order to get the most reasonable partition result, the index of clustering evaluation is ...


The Research on Robot Control Based on Fuzzy Immune Technology

Qinghao Yan; Shuhua Peng 2013 Sixth International Symposium on Computational Intelligence and Design, 2013

A new intelligent control method fuzzy control is used on the PID controller. PID control or the fuzzy PID control is hard to achieve the required control precision. The immune feedback system which develops from artificial immune system, has a strongly adaptive and stable ability is combined with the fuzzy control. The experiment result shows the fuzzy immune feedback system ...


Proposal of inspection and rescue tasks for tunnel disasters — Task development of Japan virtual robotics challenge

M. Okugawa; K. Oogane; M. Shimizu; Y. Ohtsubo; T. Kimura; T. Takahashi; S. Tadokoro 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2015

For aging social infrastructure, robot technology is effective for the inspection and maintenance. Such capabilities are similar to those required in the disaster response robots. The application of response robot technology to frequently-used maintenance robots for infrastructure accelerate the social implementation of the response robots. In the paper, the concept and outlines of Japan Virtual Robotics Challenge (JVRC) task development ...


Towards intelligent hospital devices: Health caring of patients with motor disabilities

E. Vázquez-Santacruz; R. Portillo-Flores; M. Gamboa-Zúñiga 2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 2015

In this document we present an intelligence device which includes a monitor system for automatic movements of a robotic hospital bed based on posture classification and identification. This functionality has been developed in response to the requirements defined by the application of a diagnostic methodology [10]. Our diagnostic methodology applied on a Mexican public hospital allowed us to understand that ...


Application of Reinforcement Learning to autonomous heading control for bionic underwater robots

Longxin Lin; Haibin Xie; Lincheng Shen 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2009

The bionic underwater robot propelled by undulating fins is an interesting field in current research on underwater robots. With the prosperous development of bionic underwater robots, its control problem remains big challenging for strong nonlinearity, uncertainty environments, and lack of understanding of dynamic characteristics of undulating fins. As a model-free method, the Q-learning based reinforcement learning achieves its control motivation ...


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Educational Resources on Robots

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eLearning

A partition method for UAV's envelope based on fuzzy clustering

Zhao Saifeng; Li Xiujuan; Li Chuntao 2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC), 2016

In this paper, a partition method for envelope based on fuzzy clustering is designed to obtain the typical operating points as well as the interpolation mechanism of gain scheduling according to the comparability of the dynamic characteristics and the maneuverability in some partial flight regions. In order to get the most reasonable partition result, the index of clustering evaluation is ...


The Research on Robot Control Based on Fuzzy Immune Technology

Qinghao Yan; Shuhua Peng 2013 Sixth International Symposium on Computational Intelligence and Design, 2013

A new intelligent control method fuzzy control is used on the PID controller. PID control or the fuzzy PID control is hard to achieve the required control precision. The immune feedback system which develops from artificial immune system, has a strongly adaptive and stable ability is combined with the fuzzy control. The experiment result shows the fuzzy immune feedback system ...


Proposal of inspection and rescue tasks for tunnel disasters — Task development of Japan virtual robotics challenge

M. Okugawa; K. Oogane; M. Shimizu; Y. Ohtsubo; T. Kimura; T. Takahashi; S. Tadokoro 2015 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), 2015

For aging social infrastructure, robot technology is effective for the inspection and maintenance. Such capabilities are similar to those required in the disaster response robots. The application of response robot technology to frequently-used maintenance robots for infrastructure accelerate the social implementation of the response robots. In the paper, the concept and outlines of Japan Virtual Robotics Challenge (JVRC) task development ...


Towards intelligent hospital devices: Health caring of patients with motor disabilities

E. Vázquez-Santacruz; R. Portillo-Flores; M. Gamboa-Zúñiga 2015 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 2015

In this document we present an intelligence device which includes a monitor system for automatic movements of a robotic hospital bed based on posture classification and identification. This functionality has been developed in response to the requirements defined by the application of a diagnostic methodology [10]. Our diagnostic methodology applied on a Mexican public hospital allowed us to understand that ...


Application of Reinforcement Learning to autonomous heading control for bionic underwater robots

Longxin Lin; Haibin Xie; Lincheng Shen 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO), 2009

The bionic underwater robot propelled by undulating fins is an interesting field in current research on underwater robots. With the prosperous development of bionic underwater robots, its control problem remains big challenging for strong nonlinearity, uncertainty environments, and lack of understanding of dynamic characteristics of undulating fins. As a model-free method, the Q-learning based reinforcement learning achieves its control motivation ...


More eLearning Resources

IEEE-USA E-Books

  • Monte Carlo Pose Estimation with Quaternion Kernels and the Bingham Distribution

    The success of personal service robotics hinges upon reliable manipulation of everyday household objects, such as dishes, bottles, containers, and furniture. In order to accurately manipulate such objects, robots need to know objects' full 6-DOF pose, which is made difficult by clutter and occlusions. Many household objects have regular structure that can be used to effectively guess object pose given an observation of just a small patch on the object. In this paper, we present a new method to model the spatial distribution of oriented local features on an object, which we use to infer object pose given small sets of observed local features. The orientation distribution for local features is given by a mixture of Binghams on the hypersphere of unit quaternions, while the local feature distribution for position given orientation is given by a locally-weighted (Quaternion kernel) likelihood. Experiments on 3D point cloud data of cluttered and uncluttered scenes generated from a structured light stereo image sensor validate our approach.

  • Model-Based Proprioceptive State Estimation for Spring-Mass Running

    Autonomous applications of legged platforms will inevitably require accurate state estimation both for feedback control as well as mapping and planning. Even though kinematic models and low-bandwidth visual localization may be sufficient for fully-actuated, statically stable legged robots, they are inadequate for dynamically dexterous, underactuated platforms where second order dynamics are dominant, noise levels are high and sensory limitations are more severe. In this paper, we introduce a model based state estimation method for dynamic running behaviors with a simple spring-mass runner. By using an approximate analytic solution to the dynamics of the model within an Extended Kalman filter framework, the estimation accuracy of our model remains accurate even at low sampling frequencies. We also propose two new event-based sensory modalities that further improve estimation performance in cases where even the internal kinematics of a robot cannot be fully observed, such as when flexible materials are used for limb designs. We present comparative simulation results to establish that our method outperforms traditional approaches which rely on constant acceleration motion models and that it eliminates the need for an extensive and unrealistic sensor suite.

  • Autonomous Vehicles

    This chapter contains sections titled: How Robotic Vehicles Might Help, How Autonomous Vehicles Are Developing, Complications, Autonomous Vehicle Effects, Winners, Losers, Questions We Need to Address, Conclusion

  • Morpho-Functional Machine: Robotics Approach of Amoeba Model based on Vibrating Potential Method

    Soft-mechatronics is a new research area for a developmental robotics approach. This paper reports on the methodology and results of our approach to soft-mechatronics via the imitating of mollusc-like characteristics in through both hardware and software fusion technology. The proposed approach for softmechatronics here is developing a Morpho-Functional Machine by imitating amoeba motion and structure. This paper describes the Vibrating Potential Method to control the Morpho-Functional Machine, that consists of a new field technique called the Vibrating Potential Field plus a new parameter tuning method inspired from thermodynamics. The field model creates self-organising, gathering behaviour, through physical interaction with potential fields. The computer simulation shows typical characteristics of swarm intelligence, such as, energy gathering, thermotaxis, and obstacle avoidance. Three types of robots are built with these three characteristics. This paper shows the possibility of various behaviours produced by Morpho-Functional Machine.

  • Animats in Education

    These sixty contributions from researchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fields delve into the behaviors and underlying mechanisms that allow animals and, potentially, robots to adapt and survive in uncertain environments. They focus in particular on simulation models in order to help characterize and compare various organizational principles or architectures capable of inducing adaptive behavior in real or artificial animals.Jean-Arcady Meyer is Director of Research at CNRS, Paris. Stewart W. Wilson is a Scientist at The Rowland Institute for Science, Cambridge, Massachusetts.

  • Emergent Task Allocation for Mobile Robots

    Multi-robot systems require efficient and accurate planning in order to perform mission-critical tasks. However, algorithms that find the optimal solution are usually computationally expensive and may require a large number of messages between the robots as the robots need to be aware of the global spatiotemporal information. In this paper, we introduce an emergent task allocation approach for mobile robots. Each robot uses only the information obtained from its immediate neighbors in its decision. Our technique is general enough to be applicable to any task allocation scheme as long as a utilization criteria is given. We demonstrate that our approach performs similar to the integer linear programming technique which finds the global optimal solution at the fraction of its cost. The tasks we are interested in are detecting and controlling multiple regions of interest in an unknown environment in the presence of obstacles and intrinsic constraints. The objective function contains four basic requirements of a multi-robot system serving this purpose: control regions of interest, provide communication between robots, control maximum area and detect regions of interest. Our solution determines optimal locations of the robots to maximize the objective function for small problem instances while efficiently satisfying some constraints such as avoiding obstacles and staying within the speed capabilities of the robots, and finds an approximation to global optimal solution by correlating solutions of small problems.

  • Super-Flexible Skin Sensors Embedded on the Whole Body, Self-Organizing Based on Haptic Interactions

    As robots become more ubiquitous in our daily lives, humans and robots are working in ever-closer physical proximity to each other. These close physical distances change the nature of human robot interaction considerably. First, it becomes more important to consider safety, in case robots accidentally touch (or hit) the humans. Second, touch (or haptic) feedback from humans can be a useful additional channel for communication, and is a particularly natural one for humans to utilize. Covering the whole robot body with malleable tactile sensors can help to address the safety issues while providing a new communication interface. First, soft, compliant surfaces are less dangerous in the event of accidental human contact. Second, flexible sensors are capable of distinguishing many different types of touch (e.g., hard v.s. gentle stroking). Since soft skin on a robot tends to invite humans to engage in even more touch interactions, it is doubly important that the robot can process haptic feedback from humans. In this paper, we discuss attempts to solve some of the difficult new technical and information processing challenges presented by flexible touch sensitive skin. Our approach is based on a method for sensors to self-organize into sensor banks for classification of touch interactions. This is useful for distributed processing and helps to reduce the maintenance problems of manually configuring large numbers of sensors. We found that using sparse sensor banks containing as little as 15% of the full sensor set it is possible to classify interaction scenarios with accuracy up to 80% in a 15-way forced choice task. Visualization of the learned subspaces shows that, for many categories of touch interactions, the learned sensor banks are composed mainly of physically local sensor groups. These results are promising and suggest that our proposed method can be effectively used for automatic analysis of touch behaviors in more complex tasks.

  • Warfare

    This chapter contains sections titled: Motivation, Types and Forms of Military Robots, Autonomy, Conclusion

  • Recognition and Pose Estimation of Rigid Transparent Objects with a Kinect Sensor

    Recognizing and determining the 6DOF pose of transparent objects is necessary in order for robots to manipulate such objects. However, it is a challenging problem for computer vision. We propose new algorithms for segmentation, pose estimation and recognition of transparent objects from a single RGB-D image from a Kinect sensor. Kinect's weakness in the perception of transparent objects is exploited in their segmentation. Following segmentation, edge fitting is used for recognition and pose estimation. A 3D model of the object is created automatically during training and it is required for pose estimation and recognition. The algorithm is evaluated in different conditions of a domestic environment within the framework of a robotic grasping pipeline where it demonstrates high grasping success rates compared to the state-of- the-art results. The method doesn't deal with occlusions and overlapping transparent objects currently but it is robust against non-transparent clutter.

  • Learning in Multilayer Models

    Most neural network programs for personal computers simply control a set of fixed, canned network-layer algorithms with pulldown menus. This new tutorial offers hands-on neural network experiments with a different approach. A simple matrix language lets users create their own neural networks and combine networks, and this is the only currently available software permitting combined simulation of neural networks together with other dynamic systems such as robots or physiological models. The enclosed student version of DESIRE/NEUNET differs from the full system only in the size of its data area and includes a screen editor, compiler, color graphics, help screens, and ready-to-run examples. Users can also add their own help screens and interactive menus.The book provides an introduction to neural networks and simulation, a tutorial on the software, and many complete programs including several backpropagation schemes, creeping random search, competitive learning with and without adaptive-resonance function and "conscience," counterpropagation, nonlinear Grossberg-type neurons, Hopfield-type and bidirectional associative memories, predictors, function learning, biological clocks, system identification, and more.In addition, the book introduces a simple, integrated environment for programming, displays, and report preparation. Even differential equations are entered in ordinary mathematical notation. Users need not learn C or LISP to program nonlinear neuron models. To permit truly interactive experiments, the extra-fast compilation is unnoticeable, and simulations execute faster than PC FORTRAN.The nearly 90 illustrations include block diagrams, computer programs, and simulation-output graphs.Granino A. Kom has been a Professor of Electrical Engineering at the University of Arizona and has worked in the aerospace industry for a decade. He is the author of ten other engineering texts and handbooks.



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