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Oceans 2013 - Norway

作者： Andreas J. Hausler Alessandro Saccon Antonio M. Pascoal John Hauser A. Pedro Aguiar Laboratory of Robotics and Systems in Science and Engineering Instituto Superior Tecnico Department of Mechanical Engineering Eindhoven University of Technology Electrical Computer and Energy Engineering Department University of Colorado at Boulder Faculdade de Engenharia University of Porto

ISBN: (纸本)9781479900022

There is widespread interest in the deployment of fleets of marine robots with the potential to roam the oceans freely and collect data at an unprecedented scale. This calls for the development of efficient algorithms for multiple vehicle motion planning that can take directly into account the capabilities of each vehicle as well as the environmental conditions and lend themselves to seamless integration with control and navigation systems. The latter connection is for the most part eschewed in the literature, in spite of the obvious fact that in order for the vehicles to execute the planned motions they must at a later stage navigate with great accuracy and follow the trajectories using control algorithms that take explicitly into account the dynamical constraints of the vehicles involved. Among the methods available for underwater vehicle navigation, terrain-based techniques have recently come to the fore. These techniques avoid the use of overly expensive inertial-like motion sensor units and hold considerable promise for the development of a new breed of affordable long range navigation systems. Motivated by these considerations, we tackle in the present paper the problem of multiple vehicle motion planning by taking explicitly into consideration inter-vehicle collision avoidance, together with a number of criteria that may include simultaneous times of arrival at assigned target points, energy minimization, acoustic communication constraints, and the maximization of terrain information along the vehicle paths (as measured by some appropriate criterion) for terrain-based navigation purposes.

关键词： vehicle motion planning Collision avoidance terrains Autonomous underwater vehicles Data Collection Methods Navigation systems Computer algorithms

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A Novel Extended Potential Field Controller for Use on Aerial Robots

A Novel Extended Potential Field Controller for Use on Aeria...

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IEEE International Conference on Automation science and engineering

作者： Alexander C. Woods Hung M. La Quang P. Ha Advanced Robotics and Automation Laboratory Department of Computer Science and Engineering University of Nevada Reno 89557 USA School of Electrical Mechanical and Mechatronic Systems University of Technology Sydney Australia

ISBN: (纸本)9781509024100

Unmanned Aerial Vehicles (UAV), commonly known as drones, have many potential uses in real world applications. Drones require advanced planning and navigation algorithms to enable them to safely move through and interact with the world around them. This paper presents an extended potential field controller (ePFC) which enables an aerial robot, or drone, to safely track a dynamic target location while simultaneously avoiding any obstacles in its path. The ePFC outperforms a traditional potential field controller (PFC) with smoother tracking paths and shorter settling times. The proposed ePFC's stability is evaluated by Lyapunov approach, and its performance is simulated in a Matlab environment. Finally, the controller is implemented on an experimental platform in a laboratory environment which demonstrates the effectiveness of the controller.

关键词： Drones Navigation Robot sensing systems Target tracking Stability analysis

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Adaptive Leader-Follower Formation Control of Autonomous Marine Vehicles

Adaptive Leader-Follower Formation Control of Autonomous Mar...

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IEEE Annual Conference on Decision and Control

作者： Lara Brinon-Arranz Antonio Pascoal A. Pedro Aguiar Laboratory of Robotics and Systems in Engineering and Science Instituto Superior Tecnico Technical University of Lisbon Av. Rovisco Pais 1049-001 Lisboa Portugal Faculty of Engineering of the University of Porto Porto Portugal

ISBN: (纸本)9781467360890

This paper addresses the problem of adaptive leader-follower formation control (ALFC) of autonomous marine vehicles. The rationale for this study can be found in a number of challenging geotechnical surveying missions aimed at mapping geological structures under the seabed. Mission specifications require that a group of surface vehicles equipped with acoustic receivers (hydrophones) maneuver in formation and acquire acoustic data emitted by one or more vehicles that carry acoustic emitters. To this effect, we adopt a basic setup for ALFC previously proposed for mobile robots modeled as single integrators and extend it to include explicitly the full dynamic equations of a representative type of marine vehicles. The paper offers a formal proof of convergence of the resulting formation control system. Results of simulations illustrate the performance that can be obtained with the control law proposed.

关键词： marine vehicles Ground vehicles control law formal proof Acoustic data Mobile robots

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Toward Process Controlled Medical Robotic System

arXiv

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arXiv 2023年

作者： Liu, Yihao Kheradmand, Amir Armand, Mehran The Biomechanical- and Image-Guided Surgical Systems Laboratory Laboratory for Computational Sensing & Robotics Department of Computer Science Johns Hopkins University BaltimoreMD21218 United States The Department of Neurology Department of Neuroscience Laboratory for Computational Sensing & Robotics Johns Hopkins University BaltimoreMD21218 United States The Biomechanical- and Image-Guided Surgical Systems Laboratory Laboratory for Computational Sensing & Robotics Department of Orthopaedic Surgery Department of Mechanical Engineering Department of Computer Science Applied Physics Laboratory Johns Hopkins University BaltimoreMD21218 United States

Medical errors, defined as unintended acts either of omission or commission that cause the failure of medical actions, are the third leading cause of death in the United States. Medical errors can include communication breakdowns, diagnostic errors, poor judgment, and inadequate skills. The application of autonomy and robotics can alleviate some causes of medical errors by improving accuracy and providing means to accurately follow planned procedures. However, for the robotic applications to improve safety, they must maintain constant operating conditions in the presence of disturbances, and provide reliable measurements, evaluation, and control for each state of the procedure. This article addresses the need for process control in medical robotic systems, and proposes a standardized design cycle toward its automation. Monitoring and controlling the changing conditions in a medical or surgical environment necessitates a clear definition of workflows and their procedural dependencies. We propose integrating process control into medical robotic workflows using hierarchical Finite State Machines (hFSM) to identify changes in states of the system and environment, and execute possible operations or transitions to new states. Therefore, the system translates clinician experiences and procedure workflows into machine-interpretable languages. The design cycle using hFSM formulation can be a deterministic process, which opens up possibilities for higher-level automation in medical robotics. Shown in our work, with a standardized design cycle and software paradigm, we pave the way toward controlled workflows that can be automatically generated. Additionally, a modular design for a robotic system architecture that integrates hFSM can provide easy software and hardware integration. This article discusses the system design, software implementation, and example application to Robot-Assisted Transcranial Magnetic Stimulation (RATMS) and robot-assisted femoroplasty. We also provide

关键词： Navigation systems

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Variable structure control of a redundant robotic manipulator

Variable structure control of a redundant robotic manipulato...

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IEEE International Conference on systems, Man and Cybernetics

作者： H.O. Dimo Dewen Jin Jichuan Zhang W.A. Gruver Department of Precision Instruments and Mechanology School of Mechanical Engineering Tsinghua University Beijing China Intelligent Robotics and Manufacturing Systems Laboratory School of Engineering Science Simon Fraser University Burnaby BC Canada

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Whole-body motion retargeting using constrained smoothing and functional principle component analysis

Whole-body motion retargeting using constrained smoothing an...

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IEEE-RAS International Conference on Humanoid Robots

作者： Saori Morishima Ko Ayusawa Eiichi Yoshida Gentiane Venture Department of Mechanical Systems Engineering Tokyo University of Agriculture and Technology CNRS-AIST JRL (Joint Robotics Laboratory) National Institute of Advanced Industrial Science and Technology (IS-AIST) Japan

ISBN: (纸本)9781509047192

This paper presents a novel retargeting framework for humanoid robots that allows flexible motion representation and motion synthesis with smoothing with constraints and functional principle component analysis (Functional PCA). Constrained smoothing consists in computing base functions through optimizations with constraints including mechanical limits and stability conditions. By applying Functional PCA that is a statistic method describing given motions with principal components of functions, a variety of different motions can be expressed with a small number of parameters. We apply the proposed framework to whole-body “squat” motions to reveal that those motions can practically be classified with two components. The effectiveness of the proposed method is verified by dynamic simulations and experiments with the humanoid robot HRP-4.

关键词： Principal component analysis Trajectory Smoothing methods Splines (mathematics) Humanoid robots Optimization Stability analysis

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System Calibration Towards Automated Nanomanipulation Inside Scanning Electron Microscope

System Calibration Towards Automated Nanomanipulation Inside...

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IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent systems

作者： Mingyu Wang Yaqiong Wang Zhan Yang Tao Chen Lining Sun Toshio Fukuda Jiangsu Provincial Key Laboratory of Advanced Robotics & Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Department of Micro-Nano Systems Engineering Nagoya University

ISBN: (纸本)9781538604915

This paper presented the calibration of the nanorobotic manipulator inside Scanning Electron Microscope (SEM). Repeating movement is frequently happing to reach the predetermined position and in order to realize the automated nanomanipulation inside SEM, the errors of the nanomanipultor and the system must be analyzed. A series of experiments based on SEM image feedback were conducted and the end-effectors can characterize the relationship of the two axis. An atomic force microscope (AFM) cantilever was assembled on the top of the nanorobotic manipulator, which moved straightly along the X or Y axis under stable speed. Through SEM video stream, a image processing method was used to analyze the errors of the nanomanipultor and the thermal drift of the encoder. The movement of nanomanipultor presented the good linearity and the error between the platform and the image coordinates were deteced. The slope of the x-direction is less than 1.7° and the slope of the y-direction is less than 0.8°. The nanomanipultor corrected his own track until the drift error is accumulated to 260 nm.

关键词： Scanning Electron Microscope (SEM) Nanorobot Nanomanipulation Nanorobotics Scanning Electron Microscope drift loss Atomic Force Microscopy y axis lateral axis image processing method y direction Automation Electron Microscope

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Studies of motor synergies in generating optimal goal-directed movements in human-like robotic arm

Studies of motor synergies in generating optimal goal-direct...

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IEEE International Conference on robotics and Biomimetics

作者： Kin Chung Denny Fu Yutaka Nakamura Tomoyuki Yamamoto Hiroshi Ishiguro All authors are with the Intelligent Robotics Laboratory the Department of Systems Innovation the Graduate School of Engineering Science Osaka University 1-3 Machikaneyama Toyonaka Osaka 560-8531 Japan

ISBN: (纸本)9781467321259

In studies of human motor control, motor synergy hypothesis has been proposed as a solution of the well-known degree-of-freedom problem. On the other hand, controlling complex robots using optimal control also has the increased difficulty of facing the well-known problem of dimensionality. In this paper, performance of motor synergies in application of generating goal-directed movements using optimal control is examined. Results show that computational expense could be reduced while success rate is maintained, when motor synergies with properties of achieving goal optimally are utilized. The performance of utilizing motor synergies with different properties is also investigated. It is found that the same goals can still be achieved utilizing motor synergies which possess energy efficiency properties, with satisfactory success rate and computation expense.

关键词： generating computation expense using

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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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Modeling Realistic Tool-Tissue Interactions with Haptic Feedback: A Learning-based Method

Modeling Realistic Tool-Tissue Interactions with Haptic Feed...

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International Symposium on Haptic Interfaces for Virtual Environment and Teleoperator systems (HAPTICS)

作者： Zachary Pezzementi Daniel Ursu Sarthak Misra Allison M. Okamura Engineering Research Center for Computer-Integrated Surgical Systems Technology Laboratory for Computational Science and Robotics Johns Hopkins University USA Johns Hopkins University and NIH grant USA

Surgical simulators present a safe, practical, and ethical method for surgical training. In order to enhance realism and provide the user with an immersive training experience, simulators should have the capability to provide haptic feedback to the user. High-fidelity surgical simulators also require accurate modeling of the interaction between surgical instruments and organs. Linear elasticity- based models are commonly used to simulate tool-tissue interaction due to computational considerations, although real soft tissues exhibit nonlinear viscoelastic behavior. In this paper, we use a learning algorithm to train a linear 2D mass-spring-damper system that behaves similarly to a high-fidelity nonlinear finite element (FE) model. The spring parameters are. trained off-line using data from an FE simulation of brain tissue deformation using simultaneous perturbation stochastic approximation, a model-free optimization algorithm. The model is implemented in a real-time soft tissue simulator with haptic interaction provided through the PHANTOM Omni haptic device. Our model's response is significantly closer to the desired response of the FE model than that of a linear heuristic model.

关键词： Haptic interfaces Feedback Learning systems Computational modeling Surgery Brain modeling Biological tissues Deformable models Surgical instruments Viscosity

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