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PB 13 Errors elicit high-gamma responses in the human cerebral cortex

Clinical Neurophysiology 2017年第10期128卷 e320-e320页

作者： M. Völker S. Berberich L.D.J. Fiederer J. Hammer P. Kršek M. Tomášek P. Marusic P.C. Reinacher V.A. Coenen A. Schulze-Bonhage W. Burgard T. Ball University Medical Center Freiburg iEEG and Brain Imaging Group Freiburg Germany University of Freiburg Graduate School of Robotics Freiburg Germany University of Freiburg Department of Computer Science Freiburg Germany University of Freiburg BrainLinks-BrainTools Freiburg Germany University of Freiburg Faculty of Medicine Freiburg Germany University of Freiburg Faculty of Biology Freiburg Germany Motol University Hospital Department of Neurology Prague Czech Republic University Medical Center Freiburg Stereotactic and Functional Neurosurgery Freiburg Germany University Medical Center Epilepsy Center Freiburg Germany University of Freiburg Autonomous Intelligent Systems Freiburg Germany

The nature of human error processing and the underlying cerebral mechanisms are of great interest in neuroscience, and error-related brain responses may provide information useful to improve the accuracy of brain-machine interfaces (BMIs). So far, many studies focused on error-related responses below 30 Hz. We were interested in error-related effects in the high-gamma band (HGB, 50–150 Hz), as this frequency range is thought to reflect local cortical information processing more directly than lower frequencies. 30 healthy subjects performed a flanker task as classically used to study error processing ( Gehring et al., 1993 ). Under time pressure, the subjects had to use the left or right index finger to respond to the respective flanker. Recordings of 128-channel EEG were acquired within an optimized setting for non-invasive EEG high-gamma mapping in an electromagnetically shielded cabin with full optical decoupling of all devices and high-resolution binocular eye tracking. Additionally, 9 patients with pharmacoresistant epilepsy and implanted stereo-EEG (SEEG) electrodes performed the identical task. As our main result, we show for the first time error-related HGB spectral power modulations up to 120 Hz in non-invasive EEG ( Fig. 1 A), which could also be used for decoding on a single-trial basis. Additional SEEG data ( Fig. 1 B) revealed possible sources of these effects, including the premotor cortex. Additional responses were seen in areas not reflected in the non-invasive EEG, such as hippocampus and insula. Importantly, based on the eye-tracking data, we show that the error-related effects in the gamma range cannot be explained by differences in eye movements including micro-saccades, which had a different spatial distribution compared to the error-related effects. Our findings open a new window for investigation of the complex neuronal processes related to error perception and ensuing behavioral adaptation. The similarity of intracranial and non-invasive

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The YCB object and Model set: Towards common benchmarks for manipulation research

The YCB object and Model set: Towards common benchmarks for ...

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International Conference on Advanced robotics (ICAR)

作者： Berk Calli Arjun Singh Aaron Walsman Siddhartha Srinivasa Pieter Abbeel Aaron M. Dollar Dep. of Mechanical Engineering and Materials Science Yale University New Haven CT USA Department of Computer Science University of California at Berkeley Berkeley CA USA Robotics Institute Carnegie Mellon University Pittsburgh PA USA

In this paper we present the Yale-CMU-Berkeley (YCB) Object and Model set, intended to be used for benchmarking in robotic grasping and manipulation research. The objects in the set are designed to cover various aspects of the manipulation problem; it includes objects of daily life with different shapes, sizes, textures, weight and rigidity, as well as some widely used manipulation tests. The associated database provides high-resolution RGBD scans, physical properties and geometric models of the objects for easy incorporation into manipulation and planning software platforms. A comprehensive literature survey on existing benchmarks and object datasets is also presented and their scope and limitations are discussed. The set will be freely distributed to research groups worldwide at a series of tutorials at robotics conferences, and will be otherwise available at a reasonable purchase cost.

关键词： Benchmark testing Robots Shape Grasping Databases Planning Solid modeling

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A web-based infrastructure for recording user demonstrations of mobile manipulation tasks

A web-based infrastructure for recording user demonstrations...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Ellis Ratner Benjamin Cohen Mike Phillips Maxim Likhachev Computer Science Department Bowdoin College Brunswick ME RobotWits LLC Pittsburgh PA Grasp Laboratory University of Pennsylvania Philadelphia PA Robotics Institute Carnegie Mellon University Pittsburgh PA

Learning from demonstration (LfD) is a common technique applied to many problems in robotics, such as populating grasp databases, training for reinforcement learning of high-level skill sets and bootstrapping motion planners. While such approaches are generally highly valued, they rely on the often time-consuming process of gathering user demonstrations, and hence it becomes difficult to attain a sizeable dataset. In this paper, we present a tool capable of recording large numbers of high-dimensional demonstrations of mobile manipulation tasks provided by non-experts in the field. Our tool accomplishes this via a web interface that requires no additional software to be installed beyond a web browser, as well as a scalable architecture that is capable of supporting 10 concurrent demonstrators on a single server. Our architecture employs a lightweight simulation environment to reduce unnecessary computations and improve performance. Furthermore, we show how our tool can be used to gather a large set of demonstrations of a mobile manipulation task by leveraging existing crowdsource platforms. The data set collected has been made available to the robotics community. We also present experiments in which we apply demonstrations collected through our infrastructure to teach a robot how to grasp, to teach a robot how to perform dexterous manipulation tasks such as scooping and to accelerate motion planning for full-body manipulation tasks.

关键词： Robots Mobile communication Trajectory Servers Crowdsourcing Software Computational modeling

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A real-time tracking and optimised gaze control for a redundant humanoid robot head

A real-time tracking and optimised gaze control for a redund...

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IEEE-RAS International Conference on Humanoid Robots

作者： Naresh Marturi Valerio Ortenzi Jingjing Xiao Maxime Adjigble Rustam Stolkin Ales Leonardis KUKA Robotics UK Ltd. Wednesbury UK School of Mechanical Engineering University of Birmingham Edgbaston Birmingham UK Electrical and Computer Engineering University of Birmingham Edgbaston Birmingham UK School of Computer Science University of Birmingham Edgbaston Birmingham UK

This paper addresses the problem of gaze control for a humanoid robot head. We propose a control framework comprised of two components: 1) an adaptive visual tracker that is capable of tracking an arbitrary object with unknown trajectory; 2) an optimised visual control strategy capable of controlling all joint motions of a redundant head-neck mechanism in order to retain the tracked object at image centre. The advantage of such a framework is that it does not require any prior knowledge of the object trajectory and can achieve optimal joint motions, i.e. it minimises the maximum joint motions needed to maintain constant gaze. An adaptive gain has been used with the controller in order to provide dynamic convergence of the task space error when gazing at an object with unpredictable or erratic trajectories. The proposed framework has been validated in real-time using our bi-manual humanoid robot platform Boris, and the reported experimental results demonstrate the efficiency of our approach.

关键词： Head Target tracking Kinematics Humanoid robots Visualization

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Measurement of Biomechanical Interactions at the Stump-Socket Interface in Lower Limb Prostheses

Measurement of Biomechanical Interactions at the Stump-Socke...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： V. Noll J. Wojtusch J. Schuy M. Grimmer P. Beckerle S. Rinderknecht the Institute for Mechatronic Systems in Mechanical Engineering Department of Mechnical Engineering TU Darmstadt Germany the Simulation Systems Optimization and Robotics Group Department of Computer Science TU Darmstadt Germany the Locomotion Laboratory Institute of Sport Science TU Darmstadt Germany

ISBN: (纸本)9781424492695

This paper introduces a novel measuring approach for detecting relative movement between stump and socket in lower limb prostheses. The application of the motion capturing based measuring approach is shown at a single male trans-tibial amputee using a Patella Tendon Bearing (PTB) socket. It further investigates and assesses the feasibility of measuring the relative movement between stump and socket during level walking at different velocities and allocating it to the coinciding loads. Representative results for the two translational degrees of freedom in the sagittal plane are presented and discussed. For the proximodistal (pd) direction, a linear correlation between applied load and relative movement is found, while for the anteroposterior (ap) direction the stump movement is largely influenced by the motion sequence during the respective gait event. Additionally, the effect of walking speed is discussed.

关键词： Biomechanical Interactions Stump-Socket Interface Lower Limb Prostheses

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A dependence maximization approach towards street map-based localization

A dependence maximization approach towards street map-based ...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： K. Irie M. Sugiyama M. Tomono Future Robotics Technology Center Chiba Institute of Technology Narashino-shi Chiba Japan Department of Computer Science Tokyo Institute of Technology Meguro-ku Tokyo Japan Department of Complexity Science and Engineering University of Tokyo Bunkyo-ku Tokyo

In this paper, we present a novel approach to 2D street map-based localization for mobile robots that navigate mainly in urban sidewalk environments. Recently, localization based on the map built by Simultaneous Localization and Mapping (SLAM) has been widely used with great success. However, such methods limit robot navigation to environments whose maps are prebuilt. In other words, robots cannot navigate in environments that they have not previously visited. We aim to relax the restriction by employing existing 2D street maps for localization. Finding an exact match between sensor data and a street map is challenging because, unlike maps built by robots, street maps lack detailed information about the environment (such as height and color). Our approach to coping with this difficulty is to maximize statistical dependence between sensor data and the map, and localization is achieved through maximization of a Mutual Information-based criterion. Our method employs a computationally efficient estimator of Squared-loss Mutual Information through which we achieved near real-time performance. The effectiveness of our method is evaluated through localization experiments using real-world data sets.

关键词： Robot sensing systems Roads Yttrium Feature extraction Buildings Navigation

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Balanced optical flow refinement by bidirectional constraint

Balanced optical flow refinement by bidirectional constraint

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作者： Choi, Jongwon Kim, Hyeongwoo Oh, Tae-Hyun Kweon, In So Robotics and Computer Vision Laboratory Korea Advanced Institute of Science and Technology Korea Republic of

ISBN: (纸本)9781479957514

We present an efficient optical flow refinement approach based on a bidirectional flow consistency. Our method is an add-on component that improves the existing optical flow estimation to be balanced between forward and backward flows. Most of the state-of-the-art optical flow methods only consider unidirectional motion vectors from a source image to a target image, which can make the estimated flow inconsistent with its backward estimation. The inconsistency can be reduced by considering the bidirectional motion when the optical flow is estimated, but it would be very hard for most of the typical optical flow methods and impossible for some of them. To solve this problem, we propose a sampling-based optimization method for efficiently refining the optical flows with a bidirectional constraint. By evaluating on Middle-bury benchmark and public large displacement datasets, we validate the effectiveness of our method quantitatively and qualitatively and for accuracy. © 2014 IEEE.

关键词： Optical flows

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SIMO detection schemes for underwater optical wireless communication under turbulence

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Photonics Research 2015年第3期3卷 48-53页

作者： Weihao Liu Zhengyuan Xu Liuqing Yang School of Information Science and Technology University of Science and Technology of ChinaHefeiChina State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyangChina Key Laboratory of Wireless-Optical Communications Chinese Academy of SciencesHefeiChina Department of Electrical and Computer Engineering Colorado State UniversityFort CollinsColorado 80521USA

In underwater optical wireless communication(UOWC),a channel is characterized by abundant scattering/absorption effects and optical *** previous studies on UOWC have been limited to scattering/absorption ***,experiments in the literature indicate that underwater optical turbulence(UOT)can cause severe degradation of UOWC *** this paper,we characterize an UOWC channel with both scattering/absorption and UOT taken into consideration,and a spatial diversity receiver scheme,say a singleinput–multiple-output(SIMO) scheme,based on a light-emitting-diode(LED) source and multiple detectors is proposed to mitigate deep *** Monte Carlo based statistical simulation method is introduced to evaluate the bit-error-rate performance of the *** is shown that spatial diversity can effectively reduce channel fading and remarkably extend communication range.

关键词： SIMO detection schemes for underwater optical wireless communication under turbulence than

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Effects of training data variation and temporal representation in a QSR-based action prediction system

Effects of training data variation and temporal representati...

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2014 AAAI Spring Symposium

作者： Young, Jay Hawes, Nick Intelligent Robotics Lab. School of Computer Science University of Birmingham United Kingdom

ISBN: (纸本)9781577356462

Understanding of behaviour is a crucial skill for Artificial Intelligence systems expected to interact with external agents - whether other AI systems, or humans, in scenarios involving co-operation, such as domestic robots capable of helping out with household jobs, or disaster relief robots expected to collaborate and lend assistance to others. It is useful for such systems to be able to quickly learn and re-use models and skills in new situations. Our work centres around a behaviourlearning system utilising Qualitative Spatial Relations to lessen the amount of training data required by the system, and to aid generalisation. In this paper, we provide an analysis of the advantages provided to our system by the use of QSRs. We provide a comparison of a variety of machine learning techniques utilising both quantitative and qualitative representations, and show the effects of varying amounts of training data and temporal representations upon the system. The subject of our work is the game of simulated RoboCup Soccer Keepaway. Our results show that employing QSRs provides clear advantages in scenarios where training data is limited, and provides for better generalisation performance in classifiers. In addition, we show that adopting a qualitative representation of time can provide significant performance gains for QSR systems. Copyright © 2014, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Learning systems

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Visual diver detection using multi-descriptor nearest-class-mean random forests in the context of underwater Human Robot Interaction (HRI)

Visual diver detection using multi-descriptor nearest-class-...

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OCEANS - Europe

作者： Arturo Gomez Chavez Max Pfingsthorn Andreas Birk Ivor Rendulić Nikola Misković Jacobs University Bremen Robotics Computer Science and Electrical Engineering Campus Ring 1 Bremen Germany University of Zagreb LABUST - Lab. for Underwater Systems and Technologies Unska 3 Zagreb Croatia

This paper introduces a visual method for diver detection in the context of Human Robot Interaction (HRI). The detection is treated as a classification problem, where a discriminative model is trained by computing image features of the target (diver) and underwater scenery. This type of scenery poses great challenges due to its high variability, as it often presents high illumination changes, scarce features and image distortions. For this reason, it is desirable to represent this type of images with multiple type of complementary features. The system scalability is, however, lowered as the number of features types increase as the amount of data to represent queries and indexes also increases. To remedy this, we modified the Nearest Class Mean Forests (NCMF) method, a variant of Random Forests, to integrate as many features types as desired without concerning about scalability and performance decay. The system outperforms the common generative tracking methods which fail to encompass different type of distortions into one model and ignore background information. And in contrast to tracking methods using acoustic sensors which output a single value (distance to the diver), our approach outputs a region encompassing the diver's body; information that can be further exploited to enhance underwater HRI. Not to mention that camera setups offer higher flexibility in size and energy consumption constraints than acoustic sensors. All of the system's aforementioned capabilities are tested with real-life data obtained from field experiments.

关键词： Vegetation Cameras Feature extraction Human-robot interaction Acoustics Probability density function Distortion

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