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IEEE International Conference on robotics and Automation (ICRA)

作者： Chaomin Luo S.X. Yang D.A. Stacey Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ONT Canada Department of Computing and Information Science University of Guelph Guelph ONT Canada

In this paper, a cooperative sweeping strategy with deadlock avoidance of complete coverage path planning for multiple cleaning robots in a changing and unstructured environment is proposed, using biologically inspired neural networks. Cleaning tasks require a special kind of trajectory being able to cover every unoccupied area in specified cleaning environments, which is an essential issue for cleaning robots and many other robotic applications. Multiple robots can improve the work capacity, share the cleaning tasks, and reduce the time to complete sweeping tasks. In the proposed model, the dynamics of each neuron in the topologically organized neural network is characterized by a shunting neural equation. Each cleaning robot treats the other robots as moving obstacles. The robot path is autonomously generated from the dynamic activity landscape of the neural network, the previous robot location and the other robot locations. The proposed model algorithm is computationally efficient. The feasibility is validated by simulation studies on three cases of two cooperating cleaning robots. The multiple cleaning robots sweeping will not be trapped in deadlock situations.

关键词： Path planning System recovery Cleaning Orbital robotics Robot sensing systems Intelligent robots Neural networks Computational modeling Chaos Intelligent systems

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Cooperative AUV Motion Planning using Terrain Information

Cooperative AUV Motion Planning using Terrain Information

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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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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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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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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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Trajectory Tracking of Soft Continuum Robots with Unknown Models Based on Varying Parameter Recurrent Neural Networks

Trajectory Tracking of Soft Continuum Robots with Unknown Mo...

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IEEE International Conference on systems, Man and Cybernetics

作者： Ning Tan Peng Yu Fenglei Ni Zhenglong Sun School of Computer Science and Engineering Sun Yat-sen University Guangzhou PR China State Key Laboratory of Robotics and Systems (HIT) Harbin PR China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China

ISBN: (纸本)9781665442084

Bio-inspired robots, e.g., soft continuum robots, have broad application prospects due to their structural dexterity and interaction safety. But these features also bring great challenges to the precise control of soft continuum robots. In this work, we investigate how to achieve the kinematic control of soft continuum robots without knowing model parameters of the robots. To this end, a model-free scheme based on varying-parameter recurrent neural networks (VP-RNN) is proposed. The scheme involves two components, one of which solves the inverse kinematics problem based on a VP-RNN model, and the other employs another VP-RNN model to estimate the pseudo-inverse of Jacobian matrix of continuum robots. Finally, the feasibility and robustness of the proposed control strategy are validated by simulations, including comparisons with other methods and case study with jammed actuation.

关键词： Jacobian matrices Recurrent neural networks Trajectory tracking Prototypes Kinematics Interference Robustness

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