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检索条件"任意字段=International Conference on Methods and Models in Automation and Robotics"

共 24667 条记录，以下是4731-4740 订阅

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Simulation of Robot-Assisted Flexible Needle Insertion Using Deep Q-Network

Simulation of Robot-Assisted Flexible Needle Insertion Using...

引用

IEEE international conference on Systems, Man and Cybernetics (SMC)

作者： Lee, Yonggu Tan, Xiaoyu Chng, Chin-Boon Chui, Chee-Kong Natl Univ Singapore Singapore 117575 Singapore

ISBN: (纸本)9781728145693

Flexible needle insertion with bevel tips is becoming a preferred method for approaching targets in the human body in the least invasive manner. However, to successfully implement needle insertion, surgeons require prolonged training processes and long-term experience to develop essential handling skills. 'this paper presents a new path planning approach with Deep Reinforcement Learning (DRL) to implement automatic needle insertion using a surgical robot. In this paper, Deep Q-Network (DQN) algorithm is utilized to learn the control policy for flexible needle steering with needle-tissue interaction. As the human body is composed of a complex environment such as tissues, blood vessels, bones, and muscles, the uncertainty of the needle-tissue interaction should be considered during insertion. To model this complex interaction in path planning, utilizing a neural network to approximate the action-value function is more efficient than using traditional array methods in terms of time and accuracy. In our simulation, the agent (needle) can he controlled with 2 degrees of freedom (bevel direction rotation and insertion) and received negative rewards when it collides with obstacles, goes out of range, or exceeds a predefined number of rotations. During the training, the agent demonstrates the accuracy and efficiency of the learned policy through feedback scores in every episode. In addition, this system incorporates the uncertainty within flexible needle-tissue interaction using a stochastic environment. Compared with other traditional methods for flexible needle path planning, we demonstrated that motion planning of bevel-tip flexible needles in complex human bodies using DRL has better efficiency and accuracy.

关键词： Surgical robotics: Deep Reinforcement Learning Flexible Needle Insertion Path Planning Deep Learning in robotics and automation AI Based methods

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Dynamic singularities in nonlinear control of underactuated pendulum-like models

Dynamic singularities in nonlinear control of underactuated ...

引用

international conference on methods and models in automation and robotics (MMAR)

作者： Adam Wojciech Łukomski Department of Control and Measurements West Pomeranian University of Technology Szczecin

The paper presents an analysis of dynamic singularities in n-link pendulum-like models that are controlled using input-output feedback linearisation. The dynamic singularities are caused by the decoupling matrix being singular for particular configurations. The examples include 3-link planar pendulum, 3-link 3D pendulum and a simplified humanoid-like robot model. Partial stabilisation results are presented for specific physical parameters.

关键词： Transmission line matrix methods Three-dimensional displays Solid modeling Numerical models Mathematical model Robots Knee

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Augmented Visual Localization Using a Monocular Camera for Autonomous Mobile Robots 18

Augmented Visual Localization Using a Monocular Camera for A...

引用

IEEE 18th international conference on automation Science and Engineering (IEEE CASE)

作者： Salimzadeh, Ali Bhatt, Neel P. Hashemi, Ehsan Univ Alberta Mech Engn Dept 9211-116 St NW Edmonton AB Canada Univ Waterloo Mech & Mechatron Engn Dept 200 Univ Ave W Waterloo ON Canada

ISBN: (数字)9781665490429

ISBN: (纸本)9781665490429

A visual localization method utilizing a fisheye monocular camera is proposed to enhance navigation accuracy of autonomous mobile robots in indoor environments for warehouse or service robotics applications. Existing visual infrastructure-aided localization algorithms take advantage of uniquely colored or lit robots that limit their application to ideal lighting conditions, occlusion-free scenarios or multi-modal fusion with stereo vision, LiDAR, and inertial sensors which inevitably increases their complexity. Using fisheye monocular vision imposes challenges such as depth estimation, frame warping, and low accuracy of the state estimation for far objects. The proposed augmented localization framework includes an uncertainty-aware state observer employing a motion model with a learning-based input estimator and point cloud clusters over a region of interest, to estimate the position of a robot while maintaining effective computational efficiency. Observability of the developed state estimator and asymptotic stability of the estimation error dynamics are also studied. Various tests including occlusion, low visibility for far objects, and noisy depth estimation (from the clustered region of interest), have been conducted in indoor settings to validate the method. The tests confirm robust performance of the augmented visual localization framework in presence of intermittent measurements due to environmental conditions or low reliability of vision-based depth estimation. Furthermore, a significant increase in accuracy and consistency of visual localization is shown without using additional stereo, inertial, or LiDAR measurements.

关键词： Location awareness Visualization Estimation error Robot vision systems Dynamics Estimation Predictive models

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An Iterative Neighborhood Blending Method For Multimodal Product Retrieval 2

An Iterative Neighborhood Blending Method For Multimodal Pro...

引用

2nd Asia conference on Advanced robotics, automation, and Control Engineering, ARACE 2023

作者： Liu, Qixin He, Tingqin Zhou, Zisheng Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan China

ISBN: (纸本)9798350328363

Recently, the product matching and retrieval methods based on users' real needs are becoming a hot spot in academic research, especially in the era of big data, more efficient and accurate matching methods become more necessary. Therefore, this paper aims to design an iterative neighborhood blending method for multimodal product retrieval, this method fuses image and text features of products that can efficiently retrieve items of interest to users from massive product data. First, the feature extraction model is trained by the classification head in the training stage. secondly, post-processing methods such as pooling, batch normalization and feature normalization method are designed to obtain feature vectors of different dimensions. Thirdly, product matching and retrieval are realized by an improved iterative neighborhood mixing method. Finally, experiments on the Shopee-Price dataset demonstrate that the iterative neighborhood blending algorithm brings significant improvements to the multimodal product retrieval task compared to the state-of-art. © 2023 IEEE.

关键词： Iterative methods

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Control theoretic approach to combined anticancer therapies

Control theoretic approach to combined anticancer therapies

引用

international conference on methods and models in automation and robotics (MMAR)

作者： Andrzej Świerniak Department of Automatic Control Silesian University of Technology Gliwice Poland

A model of a combination of antiangiogenic treatment and chemotherapy is proposed and analyzed. The model is a modified Hahnfeldt model and the analysis has two goals: first of all we check stability of the equilibrium point of the model to find conditions leading to tumour eradication for constant dosing and periodic treatment then we propose an optimization problem and give necessary conditions of its solution. We discuss modifications of the model which enable more realistic description of treatment effects.

关键词： Tumors Mathematical model Equations Analytical models Drugs Cancer

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Robot's Velocity and Tilt Estimation Through Computationally Efficient Fusion of Proprioceptive Sensors Readouts

Robot's Velocity and Tilt Estimation Through Computationally...

引用

international conference on methods and models in automation and robotics

作者： Pawe? Wawrzyński Institute of Control and Computation Engineering Warsaw University of Technology 00-665 Warsaw Poland

ISBN: (纸本)9781479987023

In this paper a method is introduced that combines Inertial Measurement Unit (IMU) readouts with low accuracy and temporarily unavailable velocity measurements (e.g., based on kinematics or GPS) to produce high accuracy estimates of velocity and orientation with respect to gravity. The method is computationally cheap enough to be readily implementable in sensors. The main area of application of the introduced method is mobile robotics.

关键词： velocity estimation Kalman filter mobile robotics

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Improvement to the minimization of hybrid error functions for pose alignment

Improvement to the minimization of hybrid error functions fo...

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9th international conference on Control, automation, robotics and Vision, 2006, ICARCV '06

作者： Abdul Hafez, A.H. Jawahar, C.V. Dept. of Computer Science and Engineering University College of Engineering Osmania University Hyderabad-500007 India Center for Visual Information Technology International Institute of Information Technology Gachibowli Hyderabad-500032 India

ISBN: (纸本)1424403421

Many problems in computer vision such as pose recovery and structure estimation are formulated as a minimization process. These problems vary in the use of image measurements directly or using them to extract 3D cues in the minimization process. Hybrid methods have the advantage of combining the 2D and 3D visual information to improve the performance over the above two methods. In this paper, we present a new formulation for minimizing a class of hybrid error functions. This is done by using 2D information from the image space and 3D information from the Cartesian space in one error function. Applications to visual servoing and image alignment problems are presented. The positioning task of a robot arm has been formulated as a minimization problem. Gradient decent as a first order approximation and Gauss-Newton as a second order approximation are considered in this paper. Simulation results show, comparing with 2 1/2 D hybrid method, that these two methods provide an efficient solution to the features visibility problems and the camera trajectory in the Cartesian space. © 2006 IEEE.

关键词： Image reconstruction

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Road Roughness Modelling by Using Spectral Factorization methods 16

Road Roughness Modelling by Using Spectral Factorization Met...

引用

16th international conference on Control, automation and Systems (ICCAS)

作者： Turkay, Semiha Akcay, Huseyin Anadolu Univ Dept Elect & Elect Engn Eskisehir Turkey

ISBN: (纸本)9788993215120

In this paper, road roughness model for the right and the left tracks are constructed by utilizing two methods. In the first method, from time-domain measurements the empirical auto and cross-power spectral densities of the left and the right tracks are estimated by using the Welch method. Next, the road roughness is decomposed into three stochastically independent random processes and the linear-shape filter parameters of the right and the left tracks are estimated via a recently developed subspace-based identification algorithm. In the second method, a multi-input/multi-output subspacebased identification algorithm is directly used, without employing spectral decomposition to derive the spatial-domain models of the right and the left tracks from the Welch power spectral density estimates. Profile measurements for a specific road section from the Long Term Pavement Performance archive of the University of Michigan Transportation Research Institute is used to demonstrate the successfull application of the subspace approach.

关键词： Road roughness parallel tracks power spectral density coherence estimation subspace algorithm

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Nondestructive Detection of Internal Quality of Hami Melon by Hyperspectral Technology Combined with Chemometrics

Nondestructive Detection of Internal Quality of Hami Melon b...

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2024 lEEE international conference on Advanced Information, Mechanical Engineering, robotics and automation, AIMERA 2024

作者： Li, Fengxia Yang, Quan Wang, Xiaochen Gao, Wenjun Huang, Yong Yin, Junchi University of Science and Technology Beijing Institute of Engineering Technology Beijing China Xinjiang Institute of Engineering School of Mechanical and Electrical Engineering Urumqi China

ISBN: (纸本)9798350343335

In this research, the combination of hyperspectral technology and chemometrics was applied for non-destructive testing of the internal quality of Hami melon. Sugar content and firmness serve as crucial indicators in assessing the internal quality of this fruit. Various pretreatment methods were employed for feature extraction, and subsequently, partial least squares (PLS) prediction models were established for sugar content and firmness. The outcomes reveal that the optimal results for the PLS sugar content prediction model were achieved when utilizing the original spectrum treated with multivariate scattering correction (MSC), resulting in a correlation coefficient of 0.663 and a prediction root-mean-square error of 0.909. Similarly, the PLS firmness prediction model exhibited the best performance when based on the first derivative spectrum treated with the standard normal variable transformation (SNV), yielding a correlation coefficient of 0.674 and a prediction root-mean-square error of 6.388 N. This investigation demonstrates the feasibility of employing hyperspectral technology in combination with chemometrics for simultaneous detection of the internal quality of Hami melon. The findings of this study suggest promising prospects for the future market application of the research method. The integration of hyperspectral technology and chemometrics offers a reliable and efficient approach for non-destructive evaluation of Hami melon quality, paving the way for its potential implementation in the fruit industry to ensure enhanced product quality control and consumer satisfaction. © 2024 IEEE.

关键词： Prediction models

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A variant of Adams - Bashforth - Moulton method to solve fractional ordinary differential equation

A variant of Adams - Bashforth - Moulton method to solve fra...

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international conference on methods and models in automation and robotics

作者： Marek Blasik Institute of Mathematics Czestochowa University of Technology Czestochowa Poland

In this paper, we present a numerical method to solve fractional ordinary differential equation (FDE) with Caputo derivative of order in the range (0,1]. The proposed scheme is a variant of Adams - Bashforth - Moulton... 详细信息

ISBN: (纸本)9781479987023

关键词： fractional calculus integrodifferential equations numerical methods

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