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SICE Annual Conference

作者： Takeshi Nishida Yuji Takemura Yasuhiro Fuchikawa Shuichi Kurogi Shuji Ito Masayuki Obata Norio Hiratsuka Hidekazu Miyagawa Yasuhiro Watanabe Toshinori Suehiro Yoshinori Kawamura Fujio Ohkawa Faculty of Engineering Kyushu Institute of Technology Fukuoka Japan YASKAWA INFORMATION SYSTEMS Corporation Fukuoka Japan Mechanics and Electronics Research Institute Fukuoka Industrial Technology Center Fukuoka Japan Fukuoka Industry Science and Technology Foundation Fukuoka Japan FAIS Robotics Research Institute Fukuoka Japan Faculty of Computer Science and System Engineering Kyushu Institute of Technology Fukuoka Japan

The outdoor service robot, which we call OSR-02, is presently under development intended for cleaning up urban areas by means of collecting discarded trash such as plastic bottles, cans, plastic bags and so on. Additionally, we have developed a novel sensor system for the achievement of the task by this robot; it is constructed with LRF (laser rangefinder), two cameras, and three stepping motors. In this paper, we describe the sensor system and its applications

关键词： Sensor systems Service robots Cameras Robot vision systems Robot sensing systems Robot kinematics computer industry electronics industry Plastics industry Cleaning

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Self-folded soft robotic structures with controllable joints

Self-folded soft robotic structures with controllable joints

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IEEE International Conference on robotics and Automation (ICRA)

作者： Cynthia Sung Rhea Lin Shuhei Miyashita Sehyuk Yim Sangbae Kim Daniela Rus Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA USA Department of Electronics University of York York UK Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA USA Robotics and Media Institute Korea Institute of Science and Technology Seoul South Korea

This paper describes additive self-folding, an origami-inspired rapid fabrication approach for creating actuatable compliant structures. Recent work in 3-D printing and other rapid fabrication processes have mostly focused on rigid objects or objects that can achieve small deformations. In contrast, soft robots often require elastic materials and large amounts of movement. Additive self-folding is a process that involves cutting slices of a 3-D object in a long strip and then pleat folding them into a likeness of the original model. The zigzag pattern for folding enables large bending movements that can be actuated and controlled. Gaps between slices in the folded model can be designed to provide larger deformations or higher shape accuracy. We advance existing planar fabrication and self-folding techniques to automate the fabrication process, enabling highly compliant structures with complex 3-D geometries to be designed and fabricated within a few hours. We describe this process in this paper and provide algorithms for converting 3-D meshes into additive self-folding designs. The designs can be rapidly instrumented for global control using magnetic fields or tendon-driven for local bending. We also describe how the resulting structures can be modeled and their responses to tendon-driven control predicted. We test our design and fabrication methods on three models (a bunny, a tuna fish, and a starfish) and demonstrate the method's potential for actuation by actuating the tuna fish and starfish models using tendons and magnetic control.

关键词： Fabrication Additives Geometry Algorithm design and analysis Robots Strips Tendons

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Supervised anomaly detection via conditional generative adversarial network and ensemble active learning

arXiv

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arXiv 2021年

作者： Chen, Zhi Duan, Jiang Kang, Li Qiu, Guoping School of Economic Information Engineering Southwestern University of Finance and Economics Chengdu611130 China Guangdong Key Laboratory for Intelligent Information Processing Shenzhen Institute of Artificial Intelligence and Robotics for Society College of Electronics and Information Engineering Shenzhen University Shenzhen518060 China School of Computer Science University of Nottingham NottinghamNG8 1BB United Kingdom

Anomaly detection has wide applications in machine intelligence but is still a difficult unsolved problem. Major challenges include the rarity of labeled anomalies and it is a class highly imbalanced problem. Traditional unsupervised anomaly detectors are suboptimal while supervised models can easily make biased predictions towards normal data. In this paper, we present a new supervised anomaly detector through introducing the novel Ensemble Active Learning Generative Adversarial Network (EAL-GAN). EAL-GAN is a conditional GAN having a unique one generator vs. multiple discriminators architecture where anomaly detection is implemented by an auxiliary classifier of the discriminator. In addition to using the conditional GAN to generate class balanced supplementary training data, an innovative ensemble learning loss function ensuring each discriminator makes up for the deficiencies of the others is designed to overcome the class imbalanced problem, and an active learning algorithm is introduced to significantly reduce the cost of labeling real-world data. We present extensive experimental results to demonstrate that the new anomaly detector consistently outperforms a variety of SOTA methods by significant margins. The codes are available on Github. Copyright © 2021, The Authors. All rights reserved.

关键词： Anomaly detection

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Evaluating the Effect of Speed and Acceleration on Human Factors During an Assembly Task in Human-Robot Collaboration

SSRN

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SSRN 2023年

作者： Apraiz Iriarte, Ainhoa Lasa, Ganix Mazmela, Maitane Arana-Arexolaleiba, Nestor Serrano, Antonio Elguea, Íñigo Etxabe, Amaia Design Innovation Centre Faculty of Engineering Mechanical and Industrial Production Mondragon Unibertsitatea Arrasate20500 Spain Robotics and Automation Electronics and Computer Science Department Mondragon Unibertsitatea Arrasate20500 Spain Research & Development Department Electrotécnica Alavesa S.L. Vitoria-Gasteiz1010 Spain

In Industry 5.0, the workers' well-being is the central pillar. Therefore, research on methods and technics to improve the workers' user experience in a human-robot collaborative environment is necessary. While the effects of dynamic variables, such as speed and acceleration, on human safety have been extensively studied, their impact on human perception has not been fully explored. This study investigates the effects of the robot's speed and acceleration on humans. An experimental research approach was used, where 20 participants (10 women and 10 men) performed an assembly task collaborating with a robot. Two experiments were defined, and the participants were evenly distributed: in the first experiment, the participants started by performing the task at a slow robot speed and then performed the same task at a faster speed. In the second experiment, the other half followed the opposite procedure. Key Performance Indicators (KPIs), physiological values (via EEG and GSR), and perceptual values (using the standardised UEQ-S questionnaire) were collected. The results showed that the robot's speed and acceleration impact the task's completion time and participants' emotional responses. Our results lead to a new concept, "HRI speed bell", which indicates that it is necessary to investigate the optimal speed and acceleration to ensure good trust and perceived safety. Furthermore, the task sequence also influences participants' expectations and performance. Finally, gender-differentiated results were also observed. © 2023, The Authors. All rights reserved.

关键词： Robots

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AirLoc: Object-based Indoor Relocalization

arXiv

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arXiv 2023年

作者： Aryan Li, Bowen Scherer, Sebastian Lin, Yun-Jou Wang, Chen The Department of Electronics and Communication Delhi Technological University Delhi India The Robotics Institute Carnegie Mellon University PittsburghPA15213 United States OPPO Palo AltoCA United States The Department of Computer Science and Engineering State University of New York BuffaloNY14260 United States

Indoor relocalization is vital for both robotic tasks like autonomous exploration and civil applications such as navigation with a cell phone in a shopping mall. Some previous approaches adopt geometrical information such as key-point features or local textures to carry out indoor relocalization, but they either easily fail in environment with visually similar scenes or require many database images. Inspired by the fact that humans often remember places by recognizing unique landmarks, we resort to objects, which are more informative than geometry elements. In this work, we propose a simple yet effective object-based indoor relocalization approach, dubbed AirLoc. To overcome the critical challenges of the object reidentification and remembering object relationships, we extract object-wise appearance embedding and inter-object geometric relationship. The geometry and appearance features are integrated to generate cumulative scene features. This results in a robust, accurate, and portable indoor relocalization system, which outperforms the state-of-the-art methods in room-level relocalization by 9.5% of PR-AUC and 7% of accuracy. In addition to exhaustive evaluation, we also carry out real-world tests, where AirLoc shows robustness in challenges like severe occlusion, perceptual aliasing, viewpoint shift, and deformation. Copyright © 2023, The Authors. All rights reserved.

关键词： Geometry

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Investigation of Fuzzy Models for the Valuation of Residential Premises Using the KEEL Tool

Investigation of Fuzzy Models for the Valuation of Residenti...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： Tadeusz Lasota Jacek Mazurkiewicz Bogdan Trawinski Krzysztof Trawinski Institute of Applied Informatics Wroclaw University of Technology Wroclaw Poland Faculty of Environmental Engineering and Geodesy Agricultural University of Wrocław Wroclaw Poland Wroclaw University of Technology Institute of Computer Engineering Control and Robotics Wrocław Poland Wrocław University of Technology Institute of Applied Informatics Wrocław Poland Faculty of Environmental Engineering and Geodesy Agricultural University Wroclaw Poland Faculty of Electronics Wrocław University of Technology Wrocław Poland

A series of experiments aimed to generate and learn fuzzy models for the valuation of residential premises was conducted using the KEEL tool (knowledge extraction based on evolutionary learning). Four regression and four post-processing algorithms were applied to several data sets. They referred to sales/purchase transactions of residential premises, which were derived from the cadastral system and the registry of real estate transactions. The results proved the usefulness of the tool to carry out laborious and tedious investigation in a relatively short time. Further research is needed to determine to what extent data coming from such sources allow to build the real estate valuation models.

关键词： Data models Tuning Buildings Algorithm design and analysis Data mining Floors Cost accounting

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Energy-efficient Trajectory Planning with Media Transition for a Hybrid Unmanned Aerial-Underwater Vehicle

Energy-efficient Trajectory Planning with Media Transition f...

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

作者： Pedro M. Pinheiro Armando Alves Neto Douglas G. Macharet Paulo L. J. Drews NAUTEC Center for Computational Science Universidade Federal do Rio Grande - FURG Rio Grande Brazil Dept. of Electronics Engineering Univ. Federal de Minas Gerais Belo Horizonte Brazil Dep. of Computer Science Computer Vision and Robotics Laboratory (VeRLab) Univ. Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Vehicles capable of operating in more than one environment have been developed to solve real problems. Among them, the hybrid unmanned aerial-underwater vehicle (HUAUV) is receiving attention from the robotics community, mainly with a quadrotor-like configuration. However, this vehicle presents high energy consumption because of the larger mass required compared to the only aerial vehicle, limiting its autonomy. This work addresses the trajectory planning problem for a HUAUV. The method is based on Rapidly-exploring Random Trees (RRTs), a highly customizable planning technique. In addition, we propose two new heuristics to increase the energy efficiency of the hybrid vehicle. The first consists of biasing the tree expansion towards the environment with the lowest navigation cost, while the second one assigns estimated costs to nodes in the tree and chooses the least expensive trajectories. These techniques are evaluated in physically realistic simulation experiments performed in 135 scenarios. A comparative analysis of their performances is presented relative to the state of the art. We show that using efficient heuristics can significantly contribute to reducing energy consumption and even increase the average velocity in the missions performed by these vehicles.

关键词： Energy consumption Costs Limiting Trajectory planning Navigation Media Energy efficiency Trajectory Planning Intelligent robots

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Looking around with your brain in a virtual world

Looking around with your brain in a virtual world

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IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)

作者： Danny Plass-Oude Bos Matthieu Duvinage Oytun Oktay Jaime Delgado Saa Huseyin Guruler Ayhan Istanbullu Marijn van Vliet Bram van de Laar Mannes Poel Linsey Roijendijk Luca Tonin Ali Bahramisharif Boris Reuderink HMI group Faculty of EEMCS University of Twente Netherlands TCTS Laboratory Electrical Engineering University of Mons Belgium Electronics and Communications Corlu Engineering Namik Kemal Üniversitesi Turkey IEE Group of Robotics and Intelligent Systems Universidad del Norte Colombia Faculty of Engineering and Natural Sciences VPA Laboratory Sabanci University Turkey Department of Electronics and Computer Education Faculty of Technical Education Mugla University Turkey Faculty of Computer Engineering Balikesir University Turkey Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen Nijmegen Netherlands CNBI École Polytechnique Fédérale de Lausanne Switzerland Institute for Computing and Information Sciences Radboud University Nijmegen Nijmegen Netherlands

Offline analysis pipelines have been developed and evaluated for the detection of covert attention from electroen-cephalography recordings, and the detection of overt attention in terms of eye movement based on electrooculographic measurements. Some additional analysis were done in order to prepare the pipelines for use in a real-time system. This real-time system and a game application in which these pipelines are to be used were implemented. The game is set in a virtual environment where player is a wildlife photographer on an uninhabited island. Overt attention is used to adjust the angle of the first person camera, when the player is tracking animals. When making a photograph, the animal will flee when it notices it is looked at directly, so covert attention is required to get a good shot. Future work will entail user tests with this system to evaluate usability, user experience, and characteristics of the signals related to overt and covert attention when used in such an immersive environment.

关键词： Pipelines Accuracy Electrooculography Electrodes Training Electroencephalography Games

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Accurate Prior-centric Monocular Positioning with Offline LiDAR Fusion

Accurate Prior-centric Monocular Positioning with Offline Li...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jinhao He Huaiyang Huang Shuyang Zhang Jianhao Jiao Chengju Liu Ming Liu Thrust of Robotics and Autonomous Systems The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Baidu Autonomous Driving Technology Department (ADT) Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong Department of Computer Science University College London London UK School of Electronics and Information Engineering Tongji University Shanghai China HKUST Shenzhen-Hong Kong Collaborative Innovation Research Institute Shenzhen China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Unmanned vehicles usually rely on Global Positioning System (GPS) and Light Detection and Ranging (LiDAR) sensors to achieve high-precision localization results for navigation purpose. However, this combination with their associated costs and infrastructure demands, poses challenges for widespread adoption in mass-market applications. In this paper, we aim to use only a monocular camera to achieve comparable onboard localization performance by tracking deep-learning visual features on a LiDAR-enhanced visual prior map. Experiments show that the proposed algorithm can provide centimeter-level global positioning results with scale, which is effortlessly integrated and favorable for low-cost robot system deployment in real-world applications.

关键词： Location awareness Visualization Laser radar Robot vision systems Cameras Sensor systems Robustness

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Recent Advances in Triboelectric Nanogenerators: From Technological Progress to Commercial Applications

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ACS Nano 2023年第12期17卷 11087-11219页

作者： Choi, Dongwhi Lee, Younghoon Lin, Zong-Hong Cho, Sumin Kim, Miso Ao, Chi Kit Soh, Siowling Sohn, Changwan Jeong, Chang Kyu Lee, Jeongwan Lee, Minbaek Lee, Seungah Ryu, Jungho Parashar, Parag Cho, Yujang Ahn, Jaewan Kim, Il-Doo Jiang, Feng Lee, Pooi See Khandelwal, Gaurav Kim, Sang-Jae Kim, Hyun Soo Song, Hyun-Cheol Kim, Minje Nah, Junghyo Kim, Wook Menge, Habtamu Gebeyehu Park, Yong Tae Xu, Wei Hao, Jianhua Park, Hyosik Lee, Ju-Hyuck Lee, Dong-Min Kim, Sang-Woo Park, Ji Young Zhang, Haixia Zi, Yunlong Guo, Ru Cheng, Jia Yang, Ze Xie, Yannan Lee, Sangmin Chung, Jihoon Oh, Il-Kwon Kim, Ji-Seok Cheng, Tinghai Gao, Qi Cheng, Gang Gu, Guangqin Shim, Minseob Jung, Jeehoon Yun, Changwoo Zhang, Chi Liu, Guoxu Chen, Yufeng Kim, Suhan Chen, Xiangyu Hu, Jun Pu, Xiong Guo, Zi Hao Wang, Xudong Chen, Jun Xiao, Xiao Xie, Xing Jarin, Mourin Zhang, Hulin Lai, Ying-Chih He, Tianyiyi Kim, Hakjeong Park, Inkyu Ahn, Junseong Huynh, Nghia Dinh Yang, Ya Wang, Zhong Lin Baik, Jeong Min Choi, Dukhyun Kyung Hee University Gyeonggi Yongin17104 Korea Republic of Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Department of Mechanical Engineering Soft Robotics Research Center Seoul National University Seoul08826 Korea Republic of Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Biomedical Engineering National Taiwan University Taipei10617 Taiwan Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan School of Advanced Materials Science & Engineering Sungkyunkwan University Suwon16419 Korea Republic of Sungkyunkwan University 2066 Seobu-ro Gyeonggi Suwon16419 Korea Republic of Department of Chemical and Biomolecular Engineering National University of Singapore 4 Engineering Drive 4 117585 Singapore Division of Advanced Materials Engineering Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Jeonbuk National University 567 Baekje-daero Jeonbuk Jeonju54896 Korea Republic of Department of Physics Inha University 100 Inha-ro Incheon22212 Korea Republic of School of Materials Science & Engineering Yeungnam University Gyeongbuk Gyeongsan38541 Korea Republic of 291 Daehak-ro Daejeon34141 Korea Republic of School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore Institute of Flexible Electronics Technology of Tsinghua Zhejiang Jiaxing314000 China Nanomaterials and System Lab Major of Mechatronics Engineering Faculty of Applied Energy System Jeju National University Jeju632-43 Korea Republic of School of Engineering University of Glasgow GlasgowG128QQ United Kingdom Seoul02792 Korea Republic of Department of Physics Inha University Incheon22212 Korea Republic of Suwon16419 Korea Republic of Department of

Serious climate changes and energy-related environmental problems are currently critical issues in the world. In order to reduce carbon emissions and save our environment, renewable energy harvesting technologies will serve as a key solution in the near future. Among them, triboelectric nanogenerators (TENGs), which is one of the most promising mechanical energy harvesters by means of contact electrification phenomenon, are explosively developing due to abundant wasting mechanical energy sources and a number of superior advantages in a wide availability and selection of materials, relatively simple device configurations, and low-cost processing. Significant experimental and theoretical efforts have been achieved toward understanding fundamental behaviors and a wide range of demonstrations since its report in 2012. As a result, considerable technological advancement has been exhibited and it advances the timeline of achievement in the proposed roadmap. Now, the technology has reached the stage of prototype development with verification of performance beyond the lab scale environment toward its commercialization. In this review, distinguished authors in the world worked together to summarize the state of the art in theory, materials, devices, systems, circuits, and applications in TENG fields. The great research achievements of researchers in this field around the world over the past decade are expected to play a major role in coming to fruition of unexpectedly accelerated technological advances over the next decade. © 2023 The Authors. Published by American Chemical Society

关键词： Nanogenerators

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