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作者： Becker-Asano, Christian Ogawa, Kohei Nishio, Shuichi Ishiguro, Hiroshi Intelligent Robotics and Communications Laboratory Advanced Telecommunications Research Institute Intl. 2-2-2 Hikaridai Keihanna Science City Kyoto Japan Department of Adaptive Machine Systems Osaka University Osaka Japan

ISBN: (纸本)9789728939182

This paper presents a qualitative analysis of 24 interviews with visitors of the ARS Electronica festival in September 2009 in Linz, Austria, who interacted with the android robot Geminoid HI-1, while it was tele-operated by the first author. Only 37.5% of the interviewed visitors reported an uncanny feeling with 29% even enjoying the conversation. In five cases the interviewees' feelings even changed during the interaction with Geminoid HI-1. A number of possible improvements regarding Geminoid's bodily movements, facial expressivity, and ability to direct its gaze became apparent, which inform our future research with and development of android robots.

关键词： Human robot interaction

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Geometric collision detection and potential field based time delay planning for dual arm systems

Geometric collision detection and potential field based time...

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IeeE International Conference on robotics and Automation (ICRA)

作者： Sukhan Lee H. Moradi G. Kardaras Sung-Kwon Kim Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA Department of Computer Science-EE Systems Institute for Robotics and Intelligent Systems University of Southern California Los Angeles CA USA Production Engineering Center Samsung Electronics Company Limited Suwan South Korea

In this paper a method for collision detection and collision avoidance for dual arm robots is proposed. The collision detection, a fast geometric approach based on link intersection, detects the collision and constructs the collision region for given trajectories. The time delay planning determines the minimum necessary time delay to avoid collisions using a potential field representation for collision regions. The planning is based on a flexible, massively parallel approach. It effectively avoids any local minima problems due to the potential field representation and can be used regardless of the complexity of the collision region (e.g., concave or complicated regions).

关键词： Delay effects Robotic assembly Manipulators Orbital robotics intelligent robots Parallel robots Parallel processing Assembly systems robotics and automation Path planning

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Decentralized MPC based obstacle avoidance for multi-robot target tracking scenarios

arXiv

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arXiv 2018年

作者： Tallamraju, Rahul Rajappa, Sujit Black, Michael Karlapalem, Kamalakar Ahmad, Aamir Perceiving Systems Department Max Planck Institute for Intelligent Systems Tübingen Germany Chair of Cognitive Systems Department of Computer Science University of Tubingen Tübingen Germany Agents and Applied Robotics Group International Institute for Information Technology Hyderabad India

In this work, we consider the problem of decentralized multi-robot target tracking and obstacle avoidance in dynamic environments. Each robot executes a local motion planning algorithm which is based on model predictive control (MPC). The planner is designed as a quadratic program, subject to constraints on robot dynamics and obstacle avoidance. Repulsive potential field functions are employed to avoid obstacles. The novelty of our approach lies in embedding these nonlinear potential field functions as constraints within a convex optimization framework. Our method convexifies non-convex constraints and dependencies, by replacing them as pre-computed external input forces in robot dynamics. The proposed algorithm additionally incorporates different methods to avoid field local minima problems associated with using potential field functions in planning. The motion planner does not enforce predefined trajectories or any formation geometry on the robots and is a comprehensive solution for cooperative obstacle avoidance in the context of multi-robot target tracking. Video of simulation studies: https://***/umkdm82Tt0M. Copyright © 2018, The Authors. All rights reserved.

关键词： Multipurpose robots

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Artificial buildings: Safety, complexity and a quantifiable measure of beauty

arXiv

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arXiv 2020年

作者： Mehrjou, Arash Department of Computer Science ETH Zürich & Max Planck Institute for Intelligent Systems Switzerland

A place to live is one of the most crucial necessities for all living organisms since the advent of life on planet Earth. The nature of homes has changed considerably over time. At the very early stages, human begins lived in natural places such as caves. Later on, they started to use their intelligence to build places with special purposes. Nowadays, modern technologies such as robotics and artificial intelligence have made their ways into the construction process and opened up a whole new area of opportunities and concerns that may be of interest to both technologists and philosophers. In this article, I review the evolution of buildings from fully natural to fully artificial and discuss philosophical thoughts that a fully automated construction technology may raise. I elaborate on the safety concerns of a fully automated architectural process. Then, I’ll borrow Kolmogorov complexity from algorithmic information theory to define a complexity measure for buildings. The proposed measure is then used to provide a quantifiable measure of beauty. Copyright © 2020, The Authors. All rights reserved.

关键词： Philosophical aspects

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An Efficient Medical Image Deep Fusion Model Based on Convolutional Neural Networks

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computers, Materials & Continua 2023年第2期74卷 2905-2925页

作者： Walid El-Shafai Noha A.El-Hag Ahmed Sedik Ghada Elbanby Fathi E.Abd El-Samie Naglaa F.Soliman Hussah Nasser AlEisa Mohammed E.Abdel Samea Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Security Engineering Laboratory Department of Computer SciencePrince Sultan UniversityRiyadh11586Saudi Arabia Higher Institute of Commercial Science Management Information SystemsEl-Mahala El-KobraEgypt Department of the Robotics and Intelligent Machines Faculty of Artificial IntelligenceKafrelsheikh UniversityKafr El-SheikhEgypt Department of Industrial Electronics and Control Engineering Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadhSaudi Arabia Medical Imaging and Interventional Radiology National Liver InstituteMenoufia UniversityEgypt

Medical image fusion is considered the best method for obtaining one image with rich details for efficient medical diagnosis and *** learning provides a high performance for several medical image analysis *** paper proposes a deep learning model for the medical image fusion *** model depends on Convolutional Neural Network(CNN).The basic idea of the proposed model is to extract features from both CT and MR ***,an additional process is executed on the extracted *** that,the fused feature map is reconstructed to obtain the resulting fused ***,the quality of the resulting fused image is enhanced by various enhancement techniques such as Histogram Matching(HM),Histogram Equalization(HE),fuzzy technique,fuzzy type,and Contrast Limited Histogram Equalization(CLAHE).The performance of the proposed fusion-based CNN model is measured by various metrics of the fusion and enhancement *** realistic datasets of different modalities and diseases are tested and ***,real datasets are tested in the simulation analysis.

关键词： Image fusion CNN deep learning feature extraction evaluation metrics medical diagnosis

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A review: Challenges and opportunities for artificial intelligence and robotics in the offshore wind sector

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Energy and AI 2022年第2期8卷 177-212页

作者： Daniel Mitchell Jamie Blanche Sam Harper Theodore Lim Ranjeetkumar Gupta Osama Zaki Wenshuo Tang Valentin Robu Simon Watson David Flynn Smart Systems Group Institute of SensorsSignals and SystemsSchool of Engineering and Physical SciencesHeriot-Watt UniversityEdinburghEH144ASUnited Kingdom Centre for Mathematics and Computer Science Intelligent and Autonomous Systems GroupCWIAmsterdam1098 XG Netherlands Algorithms Group Faculty of Electrical EngineeringMathematics and Computer Science(EEMCS)Delft University of Technology(TU Delft)Delft2628 XE Netherlands The University of Manchester Department of Electrical and Electronic EngineeringOxford RoadManchesterM139PL United Kingdom James Watt School of Engineering University of GlasgowG128QQUnited Kingdom

The UK has set plans to increase offshore wind capacity from 22GW to 154GW by 2030. With such tremendous growth, the sector is now looking to robotics and Artificial Intelligence (RAI) in order to tackle lifecycle service barriers as to support sustainable and profitable offshore wind energy production. Today, RAI applications are predominately being used to support short term objectives in operation and maintenance. However, moving forward, RAI has the potential to play a critical role throughout the full lifecycle of offshore wind infrastructure, from surveying, planning, design, logistics, operational support, training and decommissioning. This paper presents one of the first systematic reviews of RAI for the offshore renewable energy sector. The state-of-the-art in RAI is analyzed with respect to offshore energy requirements, from both industry and academia, in terms of current and future requirements. Our review also includes a detailed evaluation of investment, regulation and skills development required to support the adoption of RAI. The key trends identified through a detailed analysis of patent and academic publication databases provide insights to barriers such as certification of autonomous platforms for safety compliance and reliability, the need for digital architectures for scalability in autonomous fleets, adaptive mission planning for resilient resident operations and optimization of human machine interaction for trusted partnerships between people and autonomous assistants. Our study concludes with identification of technological priorities and outlines their integration into a new ‘symbiotic digital architecture’ to deliver the future of offshore wind farm lifecycle management.

关键词： Artificial intelligence Autonomous systems Digitalization Offshore renewable energy Offshore wind farms robotics

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Reference adaptive impedance control and its application to obstacle avoidance trajectory planning

Reference adaptive impedance control and its application to ...

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IeeE International Workshop on intelligent Robots and systems (IROS)

作者： S. Lee S.-Y. Yi Jong-Oh Park Chong-Won Lee Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA Department of Computer Science-EE Systems Institute of Robotics and Xntelligent Systems University of Southern California Los Angeles CA USA Korea Institute of Science and Technology Seoul South Korea

A new paradigm of event-based robotic control, called reference adaptive impedance control, is presented for partially constrained robots under uncertain or unknown environmental constraints. The reference adaptive impedance control determines the desired next state adaptively in such a way as to follow the optimal path from the current state, where the optimal path is generated with the environmental constraints updated through time. The embedded impedance control provides a mechanism for collecting more complete information on the environment. An application to obstacle avoidance trajectory planning is given with computer simulations.

关键词： Programmable control Adaptive control Impedance Trajectory Robot kinematics Robot control Error correction Force control Control systems Application software

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An adaptive P300 model for controlling a humanoid robot with mind

An adaptive P300 model for controlling a humanoid robot with...

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IeeE International Conference on robotics and Biomimetics

作者： Mengfan Li Wei Li Jing Zhao Qinghao Meng Fuchun Sun Genshe Chen The Institute of Robotics and Autonomous Systems Tianjin University Tianjin China Department of Computer & Electrical Engineering and Computer Science California State University Bakersfield California USA the Institute of Robotics and Autonomous Systems Tianjin University Tianjin China Department of Computer Science and Technology Tsinghua University Beijing China The Intelligent Fusion Technology Inc. Germantown MD

ISBN: (纸本)9781479927456

This paper presents a P300 model for controlling a humanoid robot with mind, including an off-line phase with a fixed trial number for training the model and an on-line phase with an adaptive strategy for generating commands to the humanoid robot. Our control scheme includes a procedure of acquiring P300 signals, topographical distribution analysis of P300 signals, and a classification approach to identifying subjects' mental activities regarding robot-walking behavior. Our study shows that the adaptive model is fast and practical to control humanoid robot via brainwaves.

关键词： Adaptation models Humanoid robots Accuracy Context Brain modeling Testing

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Correction to: Improving time and energy efficiency in multi-UAV coverage operations by optimizing the UAVs’ initial positions (International Journal of intelligent robotics and Applications, (2024), 10.1007/s41315-024-00333-2)

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International Journal of intelligent robotics and Applications 2024年第1期9卷 365-373页

作者： Stefanopoulou, Aliki Raptis, Emmanuel K. Apostolidis, Savvas D. Gkelios, Socratis Kapoutsis, Athanasios Ch. Chatzichristofis, Savvas A. Vrochidis, Stefanos Kosmatopoulos, Elias B. Information Technologies Institute The Centre for Research & ampTechnology Hellas 6th km Harilaou - Thermis Thessaloniki57001 Greece Department of Electrical and Computer Engineering Democritus University of Thrace Kimmeria Campus Xanthi67100 Greece Intelligent Systems Laboratory Department of Computer Science Neapolis University Pafos 2 Danais Avenue PafosCY 8042 Cyprus

In the original publication, the author has found few errors in the figures 2, 4, 11 and 12 which significantly impact both the paper's quality and the reputation of the journal. These issues undermine the clarity of the methodology and the novelty of the research. 1. Each column represents a different case in the experiment, corresponding to the number of UAVs in both the obstacle-free and obstacle areas. However, in Fig. 2, the first row contains identical subfigures across all columns, while the subfigures in the remaining rows are identical to each other The incorrect Fig. 2 appears as below: (Figure presented.) However the corrected Fig. 2 should appear as below. (Figure presented.) 2. In Fig. 4, every row showcase the average QoF for the testing scenarios (obstacle-free and obstacle area). However the first row has the exact same figures with the second row. The incorrect Fig. 4 appears as below: (Figure presented.) However the corrected Fig. 4 should appear as below. (Figure presented.) 3. Figures 11 and 12 showcase the distribution of each Quality of Flight (QoF) metric value for every UAV in the conducted trials during the testing scenarios. However, Fig. 11 is the same with Fig. 12. The incorrect Figs. 11 and 12 appears as below: (Figure presented.) However the corrected Figs. 11 and 12 should appear as below. (Figure presented.) Distribution of each Quality of Flight metric value for every UAV in the conducted trials during the coverageof the obstacle-free area Distribution of each Quality of Flight metric value for every UAV in the conducted trials during the coverageof the obstacle area The original article has been corrected. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

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Hyperbolic Delaunay Geometric Alignment

arXiv

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arXiv 2024年

作者： Medbouhi, Aniss Aiman Marchetti, Giovanni Luca Polianskii, Vladislav Kravberg, Alexander Poklukar, Petra Varava, Anastasia Kragic, Danica Division of Robotics Perception and Learning Department of Intelligent Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm100 44 Sweden

Hyperbolic machine learning is an emerging field aimed at representing data with a hierarchical structure. However, there is a lack of tools for evaluation and analysis of the resulting hyperbolic data representations. To this end, we propose Hyperbolic Delaunay Geometric Alignment (HyperDGA) – a similarity score for comparing datasets in a hyperbolic space. The core idea is counting the edges of the hyperbolic Delaunay graph connecting datapoints across the given sets. We provide an empirical investigation on synthetic and real-life biological data and demonstrate that HyperDGA outperforms the hyperbolic version of classical distances between sets. Furthermore, we showcase the potential of HyperDGA for evaluating latent representations inferred by a Hyperbolic Variational Auto-Encoder. © 2024, CC BY.

关键词： Geometry

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