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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Development an arm robot to simulate the lead-pipe rigidity for medical education

Chunbao Wang; Lihong Duan; Mengjie Li; Zhijiang Lu; Yajing Shen; Jianjun Wei; Qing Shi; Yulong Wang; Massimiliano Zecca; Weiguang Li; Zhengzhi Wu 2015 IEEE International Conference on Information and Automation, 2015

Neurologic examination takes an important role in the physical examination. It requires abundant knowledge with prominent skills. Normally, the medical staffs, especially novices are trained to master the skills and accumulate experiences with several methods such as watching video, training with the simulated patient (SP), and so on. However, the drawbacks of the above methods, such as lack of multi-symptoms, ...


A further study on kane's equations approach of robots dynamics

Ma Xiang-feng; Xu Xiang-rong Proceedings of the 1988 IEEE International Conference on Systems, Man, and Cybernetics, 1988

First Page of the Article ![](/xploreAssets/images/absImages/00754252.png)


Using aggregate motion in multi-agent teams to solve search and transport problems

A. Rodriguez; J. A. Reggia Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005., 2005

The aggregate movement of animals has inspired computational models that have proven useful for controlling navigation in teams of mobile agents. Additionally, strategies adopted from social insects have been employed in a multitude of problems to perform distributed problem solving. In this work, we combine collective movements with general problem solving capabilities to build multi-agent teams that perform search and ...


On-earth testbed for implementation of attitude control laws

Hossein Karimpour; Mojtaba Mahzoon; Mehdi Keshmiri 2011 IEEE International Conference on Mechatronics, 2011

The present attitude control testbed is intended to provide an experimental facility that, in certain senses, emulates the dynamics of in-orbit conditions and permits to evaluate path planning and feedback control algorithms for precise satellite manoeuvres in laboratory situ. This paper shows the feasibility of the approach and demonstrates how attitude control rules become compatible for both realms. Equations of ...


ElectricCow: a simulator for mobile sensors and actuators mounted on herds of cattle

D. Palmer; G. James; P. Corke 29th Annual IEEE International Conference on Local Computer Networks, 2004

ElectricCOW is a network, animal behaviour and agent simulator designed to allow detailed simulation of an ad-hoc model network built from small mote- like devices called flecks. Detailed radio communications, cattle behaviour and sensor and actuator network modelling allows a closed-loop environment, where the network can influence the behaviour of its mobile platforms.


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Educational Resources on Robots

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eLearning

Development an arm robot to simulate the lead-pipe rigidity for medical education

Chunbao Wang; Lihong Duan; Mengjie Li; Zhijiang Lu; Yajing Shen; Jianjun Wei; Qing Shi; Yulong Wang; Massimiliano Zecca; Weiguang Li; Zhengzhi Wu 2015 IEEE International Conference on Information and Automation, 2015

Neurologic examination takes an important role in the physical examination. It requires abundant knowledge with prominent skills. Normally, the medical staffs, especially novices are trained to master the skills and accumulate experiences with several methods such as watching video, training with the simulated patient (SP), and so on. However, the drawbacks of the above methods, such as lack of multi-symptoms, ...


A further study on kane's equations approach of robots dynamics

Ma Xiang-feng; Xu Xiang-rong Proceedings of the 1988 IEEE International Conference on Systems, Man, and Cybernetics, 1988

First Page of the Article ![](/xploreAssets/images/absImages/00754252.png)


Using aggregate motion in multi-agent teams to solve search and transport problems

A. Rodriguez; J. A. Reggia Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005., 2005

The aggregate movement of animals has inspired computational models that have proven useful for controlling navigation in teams of mobile agents. Additionally, strategies adopted from social insects have been employed in a multitude of problems to perform distributed problem solving. In this work, we combine collective movements with general problem solving capabilities to build multi-agent teams that perform search and ...


On-earth testbed for implementation of attitude control laws

Hossein Karimpour; Mojtaba Mahzoon; Mehdi Keshmiri 2011 IEEE International Conference on Mechatronics, 2011

The present attitude control testbed is intended to provide an experimental facility that, in certain senses, emulates the dynamics of in-orbit conditions and permits to evaluate path planning and feedback control algorithms for precise satellite manoeuvres in laboratory situ. This paper shows the feasibility of the approach and demonstrates how attitude control rules become compatible for both realms. Equations of ...


ElectricCow: a simulator for mobile sensors and actuators mounted on herds of cattle

D. Palmer; G. James; P. Corke 29th Annual IEEE International Conference on Local Computer Networks, 2004

ElectricCOW is a network, animal behaviour and agent simulator designed to allow detailed simulation of an ad-hoc model network built from small mote- like devices called flecks. Detailed radio communications, cattle behaviour and sensor and actuator network modelling allows a closed-loop environment, where the network can influence the behaviour of its mobile platforms.


More eLearning Resources

IEEE-USA E-Books

  • Distributed Self-Deployment for Forming a Desired Geometric Shape

    This chapter considers a case of the so-called flocking problem for a group of mobile robots. In flocking problems, the control objective is to cooperatively drive mobile robots from random initial locations to a formation of a desired geometric shape. The decentralized randomized control algorithm to navigate a network of autonomous mobile robotic sensors has been modified so that they collectively form a desired geometric pattern on a square grid starting from any initial deployment. In particular, a self-deployment with desired shapes such as interiors of a circle, an ellipse, a rectangle, a ring, and a regular hexagon is considered. It also proposes a randomized algorithm for self- deployment of a robotic sensor network in an unknown bounded region with obstacles. For the proposed distributed randomized algorithms, convergence with probability 1 is proved.

  • Noninvasive Estimates of Local Field Potentials for Brain-Computer Interfaces

    Recent experiments have shown the possibility of using the brain electrical activity to directly control the movement of robots or prosthetic devices in real time. Such neuroprostheses can be invasive or noninvasive, depending on how the brain signals are recorded. In principle, invasive approaches will provide a more natural and flexible control of neuroprostheses, but their use in humans is debatable given the inherent medical risks. Noninvasive approaches mainly use scalp electroencephalogram (EEG) signals and their main disadvantage is that these signals represent the noisy spatiotemporal overlapping of activity arising from very diverse brain regions, that is, a single scalp electrode picks up and mixes the temporal activity of myriad neurons at very different brain areas. To combine the benefits of both approaches, we propose to rely on the noninvasive estimation of local field potentials (eLFP) in the whole human brain from the scalp-measured EEG data using a recently developed inverse solution (ELECTRA) to the EEG inverse problem. The goal of a linear inverse procedure is to deconvolve or unmix the scalp signals attributing to each brain area its own temporal activity. To illustrate the advantage of this approach, we compare, using identical sets of spectral features, classification of rapid voluntary finger self-tapping with left and right hands based on scalp EEG and eLFP on three subjects using different numbers of electrodes. It is shown that the eLFP-based Gaussian classifier outperforms the EEG-based Gaussian classifier for the three subjects.

  • Lying Pose Recognition for Elderly Fall Detection

    This paper proposes a pipeline for lying pose recognition from single images, which is designed for health-care robots to find fallen people. We firstly detect object bounding boxes by a mixture of viewpoint-specific part based model detectors and later estimate a detailed configuration of body parts on the detected regions by a finer tree-structured model. Moreover, we exploit the information provided by detection to infer a reasonable limb prior for the pose estimation stage. Additional robustness is achieved by integrating a viewpoint-specific foreground segmentation into the detection and body pose estimation stages. This step yields a refinement of detection scores and a better color model to initialize pose estimation. We apply our proposed approach to challenging data sets of fallen people in different scenarios. Our quantitative and qualitative results demonstrate that the part-based model significantly outperforms a holistic model based on same feature type for lying pose detection. Moreover, our system offers a reasonable estimation for the body configuration of varying lying poses.

  • Expert Systems: A Discussion

    What is the bottom line on Artificial Intelligence? The AI Business offers a comprehensive summary of the commercial picture, present and future, for Artificial Intelligence in the computer industry, medicine, the oil industry, and electronic design. AI's brightest and best -- financiers, researchers, and users -- analyze current projects, speculate on trends in factory automation, compare research in Japan and the U.S., and note the pros and cons of investment opportunities.Contents: Expert Systems. Amplifying Expertise with Expert Systems, Randall Davis (MIT). XCON: An Expert Configuration System at Digital Equipment Corporation, Arnold Kraft (DEC). DIPMETER ADVISOR: An Expert Logo Analysis System at Schlumberger, James D. Baker (Schlumberger). CADUCEUS: An Experimental Expert System for Medical Diagnosis, Harry E. Pople, Jr. (University of Pittsburgh). The Low Road, the Middle Road, and the High Road, John Seely Brown (Xerox).Work and Play. Inventing the Future, Alan Kay (Atari). The Engineer's Apprentice, Aryeh Finegold (Daisy Systems Corporation). The Programmer's Apprentice, Charles Rich (MIT). Intelligent Advisory Systems, Roger Schank (Cognitive Systems, Inc. and Yale University). Natural Language Front Ends, Larry R. Harris (Artificial Intelligence Corporation).Robotics. Intelligent Robots: Connecting Perception to Action, ). Michael Brady (MIT). Intelligent Robots: Moving toward Megassembly, Philippe Villers (Automatix, Inc.). Intelligent Robots: Myth or Reality, Paul M. Russo (GE).Today and Tomorrow. The Problems and the Promise, Marvin Minsky (MIT). An Investment Opportunity? Frederick R. Adler (Adler & Company). Financing the Future, William H. Janeway (F. Eberstadt & Co., Inc.) From the Blocks World to the Business World, Patrick H. Winston and Karen A. Prendergast (MIT). How to Learn More.

  • Competitive co-evolution

    This chapter contains sections titled: Introduction, Co-evolutionary complications, Co-evolving predator and prey robots, Evolution of predator and prey robots: a basic experiment, Testing individuals against all discovered solutions, How the length of "arms races" may vary in different conditions, How co-evolution can enhance the adaptive power of artificial evolution, The role of ontogenetic plasticity in co-evolution, Conclusions

  • On social laws for artificial agent societies: off-line design

    We are concerned with the utility of social laws in a computational environment, laws which guarantee the successful coexistence of multiple programs and programmers. In this paper we are interested in the off-line design of social laws, where we as designers must decide ahead of time on useful social laws. In the first part of this paper we suggest the use of social laws in the domain of mobile robots, and prove analytic results about the usefulness of this approach in that setting. In the second part of this paper we present a general model of social law in a computational system, and investigate some of its properties. This includes a definition of the basic computational problem involved with the design of multi-agent systems, and an investigation of the automatic synthesis of useful social laws in the framework of a model which refers explicitly to social laws.

  • Work and Play

    What is the bottom line on Artificial Intelligence? The AI Business offers a comprehensive summary of the commercial picture, present and future, for Artificial Intelligence in the computer industry, medicine, the oil industry, and electronic design. AI's brightest and best -- financiers, researchers, and users -- analyze current projects, speculate on trends in factory automation, compare research in Japan and the U.S., and note the pros and cons of investment opportunities.Contents: Expert Systems. Amplifying Expertise with Expert Systems, Randall Davis (MIT). XCON: An Expert Configuration System at Digital Equipment Corporation, Arnold Kraft (DEC). DIPMETER ADVISOR: An Expert Logo Analysis System at Schlumberger, James D. Baker (Schlumberger). CADUCEUS: An Experimental Expert System for Medical Diagnosis, Harry E. Pople, Jr. (University of Pittsburgh). The Low Road, the Middle Road, and the High Road, John Seely Brown (Xerox).Work and Play. Inventing the Future, Alan Kay (Atari). The Engineer's Apprentice, Aryeh Finegold (Daisy Systems Corporation). The Programmer's Apprentice, Charles Rich (MIT). Intelligent Advisory Systems, Roger Schank (Cognitive Systems, Inc. and Yale University). Natural Language Front Ends, Larry R. Harris (Artificial Intelligence Corporation).Robotics. Intelligent Robots: Connecting Perception to Action, ). Michael Brady (MIT). Intelligent Robots: Moving toward Megassembly, Philippe Villers (Automatix, Inc.). Intelligent Robots: Myth or Reality, Paul M. Russo (GE).Today and Tomorrow. The Problems and the Promise, Marvin Minsky (MIT). An Investment Opportunity? Frederick R. Adler (Adler & Company). Financing the Future, William H. Janeway (F. Eberstadt & Co., Inc.) From the Blocks World to the Business World, Patrick H. Winston and Karen A. Prendergast (MIT). How to Learn More.

  • Individualized Automation

    This chapter contains sections titled: A Shoemaking Scenario, Programmable Robots and Vision, Future Prospects of Automatic Control Systems, Networks and Integrated Automation Systems, Some Socioeconomic Observations, Editors' Postscript

  • The Motion Grammar: Linguistic Perception, Planning, and Control

    We present and analyze the Motion Grammar: a novel unified representation for task decomposition, perception, planning, and control that provides both fast online control of robots in uncertain environments and the ability to guarantee completeness and correctness. The grammar represents a policy for the task which is parsed in real-time based on perceptual input. Branches of the syntax tree form the levels of a hierarchical decomposition, and the individual robot sensor readings are given by tokens. We implement this approach in the interactive game of Yamakuzushi on a physical robot resulting in a system that repeatably competes with a human opponent in sustained gameplay for the roughly six minute duration of each match.

  • Global Motion Planning under Uncertain Motion, Sensing, and Environment Map

    Motion planning that takes into account uncertainty in motion, sensing, and environment map, is critical for autonomous robots to operate reliably in our living spaces. Partially Observable Markov Decision Processes (POMDPs) is a principled and general framework for planning under uncertainty. Although recent development of point-based POMDPs have drastically increased the speed of POMDP planning, even the best POMDP planner today, fails to generate reasonable motion strategies when the environment map is not known exactly. This paper presents Guided Cluster Sampling (GCS), a new point-based POMDP planner for motion planning under uncertain motion, sensing, and environment map, when the robot has active sensing capability. It uses our observations that in this problem, the belief space B can be partitioned into a collection of much smaller subspaces, and an optimal policy can often be generated by sufficient sampling of a small subset of the collection. GCS samples B using two-stage cluster sampling, a subspace is sampled from the collection and then a belief is sampled from the subspace. It uses information from the set of sampled sub-spaces and sampled beliefs to guide subsequent sampling. Preliminary results suggest that GCS generates reasonable policies for motion planning problems with uncertain motion, sensing, and environment map, that are unsolvable by the best point-based POMDP planner today, within reasonable time. Furthermore, GCS handles POMDPs with continuous state, action, and observation spaces. We show that for a class of POMDPs that often occur in robot motion planning, GCS converges to the optimal policy, given enough time. To the best of our knowledge, this is the first convergence result for point- based POMDPs with continuous action space.



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