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2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Young-Hoon Nho Jong Gwan Lim Dae-Eon Kim Dong-Soo Kwon Robotics Program and Human-Robot Interaction research center Korea Advanced Institute of Science and Technology Daejeon Republic of Korea Department of Information Engineering Computer Science and University of Trento Italy KAIST Human-Robot Interaction Research Center Daejeon Republic of Korea Department of Mechanical Engineering Human-Robot Interaction research center Daejeon Republic of Korea

Fall detection systems have been proposed to prevent additional injuries following fall accidents. This paper introduces an easily learnable fall detection system based on the data of an individual patient in a hospital room. The improvement of low performance using a single accelerometer at wrists and the inconvenience of sensor attached to a waist in the conventional approach was concentrated on by integrating heart rate signals to the conventional acceleration approach and changing the sensor location from a waist to wrists. As for the optimal heart rate feature selection, we proposed a four-feature vector combination (root mean square of successive differences, standard deviation of successive differences, normal to normal 50, normal to normal 20) with correlation and mutual information analysis in addition to mean absolute deviation selected as an accelerometer feature. To easily acquire and train the patients' fall data, our system was based on unsupervised learning approaches using Gaussian mixture models for optimal classifiers with the optimal cluster number decided by cluster validation index of square error sum. A 10-fold cross validation was applied for a final performance evaluation where each threshold for separating fall state from non-fall state was automatically decided in several comparison groups, which were created on the basis of fusion timing and used sensors. As a result, despite sensors attached to the wrist, the wearable inconvenience of the conventional is overcome using the feature-level fused approach between heart rates and accelerations with the accuracy up to 98.39 %, which is closest to 99.34 % of the case using a single accelerometer located at the waist.

关键词： Accelerometers Heart rate Wrist Training data Hospitals Robot sensing systems Unsupervised learning

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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Underwater Visual SLAM with Loop-Closure using Image-to-Image Link Recovery

Underwater Visual SLAM with Loop-Closure using Image-to-Imag...

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OCEANS

作者： Seonghun Hong Taeyun Kim Jinwhan Kim Robotics Program Department of Mechanical Engineering KAIST Daejeon Korea

ISBN: (纸本)9781479987375

This study develops an underwater visual simultaneous localization and mapping (SLAM) algorithm using a monocular vision as a major measurement sensor, focusing in particular on the loop-closure problem. Although most vision-based loop-closure approaches have been implemented by feature-based pairwise image matching, matching underwater images is generally a challenging task due to the limited number of feature correspondences or relatively small overlapping regions between the compared images. The lack of loop-closing events caused by these challenges can degrade the navigation and mapping performance of visual SLAM. For robust visual SLAM, a loop-closure algorithm that can recover image-to-image matching links is presented. The proposed loop-closure algorithm is more resilient to failures of pairwise matching and thus can maximize the use of image-to-image links, thereby improving the estimation performance in the context of visual SLAM. To validate the effectiveness of the proposed algorithm, a hover-capable unmanned underwater vehicle was used for in-water experiments, and the proposed algorithm was also evaluated through a series of comparative results drawn from an experimental dataset.

关键词： Underwater visual SLAM Loop-closure Link recovery

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Optimization of fish-like locomotion using hierarchical reinforcement learning

Optimization of fish-like locomotion using hierarchical rein...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Jeonghyeon Wang Jinwhan Kim Robotics Program Ocean Robotics & Intelligence (ORIN) Laboratory Department of Mechanical Engineering KAIST Daejeon Korea

With an interest in advanced marine propulsion systems, much research has been done on mimicking fish-like locomotion using flapping fins. This study aims to optimize the swimming pattern of fish-like locomotion based on hierarchical reinforcement learning. A simplified carangiform fish model is employed and a segmented tail motion is learned by Q-learning to maximize the average forward velocity by flapping the tail fin. The performance of the self-learned swimming pattern is verified and analyzed in terms of the flapping efficiency. The results show that the flapping angle limit of approximately 35 degrees is best in maximizing the forward moving velocity and the hierarchical reinforcement learning approach is effective in providing a reasonable solution for a large-scale problem.

关键词： Learning (artificial intelligence) Learning systems Mathematical model Markov processes Robots Propulsion

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Feedforward augmented sliding mode motion control of antagonistic soft pneumatic actuators

Feedforward augmented sliding mode motion control of antagon...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Erik H. Skorina Ming Luo Selim Ozel Fuchen Chen Weijia Tao Cagdas D. Onal Mechanical Engineering Department and Robotics Engineering Program Worcester Polytechnic Institute MA USA

ISBN: (纸本)9781479969241

Soft pneumatic actuators provide many exciting properties, but controlling them without the use of bulky and expensive flow-control valves can be difficult and computationally expensive. We seek a solution to this problem by introducing an inexpensive and reliable muscle-like linear soft actuator used antagonistically to operate a rigid 1-DoF joint, resulting in a system that combines the advantages of rigid and soft robotics. Using this setup, we performed precise motion control using a sliding mode feedback controller as well as a sliding mode controller augmented by a feedforward term to modulate the state of solenoid valves that drive each actuator. We found that both controllers performed equivalently well in following a step function and in responding to a disturbance. The feedforward augmented controller performed significantly better when following dynamic trajectories over a range of frequencies and with the addition of an external force. The next step will be to modify our valve control scheme to allow for the determination of both the position and stiffness of the joint, better leveraging the advantages of soft pneumatic actuators.

关键词： Actuators Joints Valves Pulse width modulation Rubber Motion control Solenoids

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programmable Skins based on Core-Shell Microsphere/Nanotube/Polymer Composites

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MRS Online Proceedings Library 2015年第1期1800卷 1-6页

作者： Panchapakesan, Balaji Onal, Cagdas Loomis, James Small Systems Laboratory Department of Mechanical Engineering Worcester Polytechnic Institute Worcester USA Soft Robotics Laboratory Department of Mechanical Engineering Robotics Engineering Program Worcester Polytechnic Institute Worcester USA Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge USA

In this paper, we describe unique thermally responsive polymer system based on nanotube-elastomers dispersed with core-shell expanding microspheres (phase-change material). Upon thermal or infrared stimuli, liquid hydrocarbon cores encapsulated within the microspheres vaporize, expanding the surrounding shells and stretching the matrix. Microsphere transformation resulted in visible dimensional changes associated with macroscopic volume increase (>500%), reduction in density (>80%), and increase in elastic modulus (>675%). Additionally, electrically conductive nanotubes allowed for expansion dependent electrical responses. We present our new findings on expansion dependent superhydrophobicity in these materials and present some outlook and comparison of our stimuli responsive polymers with other material systems for future origami based applications.

关键词： actuator composite nanostructure

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Fuzzy gaze control-based navigational assistance system for visually impaired people in a dynamic indoor environment

Fuzzy gaze control-based navigational assistance system for ...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Seung-Beom Han Deok-Hwa Kim Jong-Hwan Kim Robotics Program KAIST Daejeon Korea Department of Electrical Engineering KAIST Daejeon Korea

285 million people are estimated to be visually impaired worldwide. Visually impaired people typically use a white cane or a guide dog or both of them to walk down the street. However, such as a cane and/or a dog are not enough to secure them from being collided with obstacles in a dynamic environment. This paper proposes a navigational assistance system based on fuzzy integral-based gaze control for visually impaired people in a dynamic indoor environment. It largely consists of an RGB-D camera and a vibrotactile vest interface. The RGB-D camera detects static and dynamic obstacles and obtains obstacle information on their center positions, sizes, and velocities. The fuzzy integral-based gaze control for obstacle detection is proposed to reduce a blind spot of the camera and obtain more information of the environment. The vibrotactile vest interface notifies a direction to avoid the obstacle using a fuzzy integral-based imminent-obstacle selection algorithm. To confirm the performance of the proposed assistance system for visually impaired people, experiments are carried out in an indoor dynamic environment.

关键词： Cameras 5G mobile communication Navigation Heuristic algorithms Indoor environments Visualization Size measurement

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Detection and Segmentation of Underwater Archaeological Sites Surveyed with Stereo-Vision Platforms

Detection and Segmentation of Underwater Archaeological Site...

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Oceans MTS/IEEE Washington (Conference)

作者： Katherine A. Skinner Matthew Johnson-Roberson Robotics Program University of Michigan Department of Naval Architecture and Marine Engineering University of Michigan

ISBN: (纸本)9781467393744

This paper proposes a method for automating detection and segmentation of archaeological structures in underwater environments. Underwater archaeologists have recently taken advantage of robotic or diver-operated stereo-vision platforms to survey and map submerged archaeological sites. From the acquired stereo images, 3D reconstruction can be performed to produce high-resolution photo-mosaic maps that are metrically accurate and contain information about depth. Archaeologists can then use these maps to manually outline or sketch features of interest, such as building plans of a submerged city. These features often contain large rocks that serve as the foundation to buildings and are arranged in patterns and geometric shapes that are characteristic of human-made structures. Our proposed method first detects these large rocks based on texture and depth information. Next, we exploit the characteristic geometry of human-made structures to identify foundation rocks arranged along lines to form walls. Then we propose to optimize the outlines of these walls by using the gradient of depth to seek the local minimum of the height from the seafloor to identify the ground plane at the base of the rocks. Finally, we output contours as geo-referenced layers for geographic information system (GIS) and architectural planning software. Experiments are based on a 2010 stereo reconstruction survey of Pavlopetri, a submerged city off the coast of Greece. The results provide a proof-of-concept for automating extraction of archaeological structure in underwater environments to produce geo-referenced contours for further analysis by underwater archaeologists.

关键词： Rocks Image segmentation Image reconstruction Dictionaries Training Three-dimensional displays Buildings

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Development of USV Autonomy for the 2014 Maritime RobotX Challenge

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IFAC-PapersOnLine 2015年第16期48卷 13-18页

作者： Minju Kang Sungchur Kwon Jeonghong Park Taeyun Kim Jungwook Han Jeonghyeon Wang Seonghun Hong Yeonjoo Shim Sukmin Yoon Byunghyun Yoo Jinwhan Kim Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Robotics Program Korea Advanced Institute of Science and Technology Daejeon Korea

The inaugural Maritime RobotX Challenge competition was held in Marina Bay, Singapore between October 20-26 in 2014. The competition composed of five mission tasks in which intelligence is the single most important factor, and all the mission tasks were required to be performed autonomously with no human intervention. We participated in the competition as the KAIST team with our own unmanned surface vehicle integrated with various sensors for autonomous navigation and perception. All the software algorithms for vehicle autonomy including mission management, environmental perception, path planning and control were developed and applied in the actual competition. This paper describes the given mission tasks of the competition and how the vehicle intelligence and control algorithms were designed in order to perform those mission tasks autonomously.

关键词： Unmanned surface vehicle vehicle autonomy navigation perception

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Dynamic object tracking of a quad-rotor with image processing and an extended Kalman filter

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Journal of Institute of Control, robotics and Systems 2015年第7期21卷 641-647页

作者： Kim, Ki-jung Yu, Ho-Yun Lee, Jangmyung Department Interdisciplinary Program in Robotics Pusan National University Korea Republic of Depart of Electrical Engineering Pusan National University Korea Republic of

This paper proposes a new strategy for a quad-rotor to track a moving object efficiently by using image processing and an extended Kalman filter. The goal of path planning for the quad-rotor is to design an optimal path from the start point to the destination point. To lengthen the freight time of the quad-rotor, an optimal path is required to reduce the energy consumption. To track a moving object, the mark signed on the moving object has been detected by a camera mounted first on the quad-rotor. The center coordinates of the mark and its area are calculated through the blob analysis which is one type of image processing. The mark coordinates are utilized to obtain information on the motion direction and the area of the mark is utilized to recognize whether the object moves backward or forward from the camera on the quad-rotor. In addition, an extended Kalman filter has been applied to predict the direction and speed of the dynamically moving object. Through these schemes, it is aimed that the quad-rotor can track the dynamic object efficiently in terms of flight distance and time. Through the two different route freights of the quad-rotor, the performance of the proposed system has been demonstrated. © ICROS 2015.

关键词： Extended Kalman filters

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