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16th International Workshop on Breast Imaging, IWBI 2022

作者： Vidal, Joel Martí, Robert Computer Vision and Robotics Institute University of Girona Girona Spain

ISBN: (纸本)9781510655843

Triple-negative is one of the most aggressive type of breast cancer for which is also difficult to find an effective treatment. An early diagnosis and a fast and specific treatment are shown to be key aspects for a better prognosis. Current diagnosis of these cases are based on performing a biopsy. This study proposes a non-invasive medical imaging predication method, based on a deep learning architecture, to automatically classify triple-negative tumors in DCE-MRI images. Results are evaluated on an extensive public dataset for different normalizations, data augmentations, learning rates and batch sizes, reaching a state-of-the-art AUC of 0.68. © 2022 SPIE.

关键词： Diseases

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Comparative Analysis of Linear and Exact Control Laws in Zonotope-Based MPC 8

Comparative Analysis of Linear and Exact Control Laws in Zon...

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8th Scientific School "Dynamics of Complex Networks and their Applications", DCNA 2024

作者： Jnadi, Ali Savin, Sergei Institute of Robotics and Computer Vision Innopolis University Innopolis Russia

ISBN: (纸本)9798350390834

Zonotopes are a special type of symmetric polytopes that have been an emerging control design tool, being used for such tasks as state estimation and explicit model predictive control. Zonotopes are used to represent sets of control actions and states, encountered by trajectories of the system, originating from a set of initial conditions. However, an inherent limitation of zonotope geometry (their symmetries, for example) limits the range of control design scenarios where zonotopes can be used as an adequate set representation, while the use of linear control laws can prevent change in the desired behavior of the closed-loop system. The first issue can be remedied by the use of constrained zonotopes, which can represent arbitrary polytopes. In this paper we present an analysis of the second problem, demonstrating the effects of linear control law and exact, convex programmingbased control law. We demonstrate the efficacy of the use of the lifting-up method for constrained zonotopes as pertains to control design. © 2024 IEEE.

关键词： Constrained optimization

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Motion Planning of Quadruped Robot Using Potential Field

Motion Planning of Quadruped Robot Using Potential Field

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2021 International Conference "Nonlinearity, Information and robotics", NIR 2021

作者： Voeurn, Yong Ann Raza, Muhammad Ilyas Innopolis University Institute of Robotics and Computer Vision Innopolis Russia

ISBN: (纸本)9781665424066

In motion planning, there are two main emerged directions which are inverse kinematics and control. In this paper, we present the derivation of motion control for a quadruped robot. We proposed inverse kinematics for obstacle avoidance trajectory planning using potential fields. The proposed inverse kinematics is capable of solving a wide range of complex movement skills to quadruped and provides robustness to the singularity configuration. In the control part, we derived LQR control of linearized inverse dynamics with constraints. The proposed algorithm is tested in various experiment cases in both fixed and free moving of center mass(CoM). © 2021 IEEE.

关键词： Inverse kinematics

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A deep learning based robot positioning error compensation

A deep learning based robot positioning error compensation

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2021 International Conference "Nonlinearity, Information and robotics", NIR 2021

作者： Sellami, Sami Klimchik, Alexandr Innopolis University Institute of Robotics and Computer Vision Innopolis Russia

ISBN: (纸本)9781665424066

Robot position accuracy plays a very important role in advanced industrial applications, nowadays, most of the industrial robots have excellent repeatability, however, it still always remain some absolute position error that are due to non geometric calibration parameters that are hard to model and identify. The present work studied a method to reduce the absolute position error of robots using conventional identification procedures as well as neural networks. In order to increase the robot accuracy, we propose to first identify determinable error sources (geometric errors and joint deflection errors), then, use deep learning based methods to identify the non-geometric error sources such as link compliance, gear backlash, and others, which are difficult to model correctly and completely. The algorithm is tested on simulation with the UR-10 robot and is able to identify some predefined parameters with a high level of accuracy using only measurements data and deep learning methods. © 2021 IEEE.

关键词： Industrial robots

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Deep Learning Based Segmentation of Breast Lesions in DCE-MRI 25th

Deep Learning Based Segmentation of Breast Lesions in DCE-MR...

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25th International Conference on Pattern Recognition Workshops, ICPR 2020

作者： Khaled, Roa’a Vidal, Joel Martí, Robert Computer Vision and Robotics Institute University of Girona Girona Spain

ISBN: (纸本)9783030687625

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) is a popular tool for the diagnosis of breast lesions due to its effectiveness, especially in a high risk population. Accurate lesion segmentation is an important step for subsequent analysis, especially for computer aided diagnosis systems. However, manual breast lesion segmentation of (4D) MRI is time consuming, requires experience, and it is prone to interobserver and intraobserver variability. This work proposes a deep learning (DL) framework for segmenting breast lesions in DCE-MRI using a 3D patch based U-Net architecture. We perform different experiments to analyse the effects of class imbalance, different patch sizes, optimizers and loss functions in a cross-validation fashion using 46 images from a subset of a challenging and publicly available dataset not reported to date, that is the TCGA-BRCA. We also compare the proposed U-Net framework with another state-of-the-art approach used for breast lesion segmentation in DCE-MRI, and report better segmentation accuracy with the proposed framework. The results presented in this work have the potential to become a publicly available benchmark for this task. © 2021, Springer Nature Switzerland AG.

关键词： Magnetic resonance imaging

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Parameter Identification in Mechanical Systems with Energy-Based Regressor: Preliminary Study

Parameter Identification in Mechanical Systems with Energy-B...

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2021 International Conference "Nonlinearity, Information and robotics", NIR 2021

作者： Sabirova, Adelia Nedelchev, Simeon Gaponov, Igor Innopolis University Institute of Robotics and Computer Vision Innopolis Russia

ISBN: (纸本)9781665424066

Parameter estimation in physical systems is an important area of modern engineering and robotics. This paper discusses parameter identification in linear, time-invariant mechanical systems based on their energy. The described approach employs system's regressor derived from the energy equation with subsequent least-squares estimation. This method has been evaluated experimentally on a single degree-of-freedom pendulum and demonstrated high accuracy and quick parameter convergence, while not suffering from the drawbacks of conventional dynamics-based identification. © 2021 IEEE.

关键词： Degrees of freedom (mechanics)

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Underwater 3D laser scanners: The deformation of the plane

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Workshop on Sensing and Control for Autonomous Vehicles: Applications to Land, Water and Air Vehicles, 2017

作者： Palomer, Albert Ridao, Pere Ribas, David Forest, Josep Computer Vision and Robotics Institute Universitat de Girona Girona Spain

ISBN: (纸本)9783319553719

Development of underwater 3D perception is necessary for autonomous manipulation and mapping. Using a mirror-galvanometer system to steer a laser plane and using triangulation, it is possible to produce full 3D perception without the need of moving the sensor. If the sensor does not meet certain hardware requirements, the laser plane is distorted when it passes through the different media (air–viewport– water). However, the deformation of this plane has not been studied. In this work a ray-tracing model is presented to study the deformation of the laser plane. To validate it, two types of datasets have been used, one synthetically generated using the model presented below, and another one using real data gathered underwater with an actual laser scanner. For both datasets an elliptic cone is fitted on the data and compared to a plane fit (the surface commonly used for triangulation). In the two experiments, the elliptic cone proved to be a better fit than the plane. © Springer International Publishing AG 2017.

关键词： Triangulation

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Free-floating panel intervention by means of learning by demonstration

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IFAC-PapersOnLine 2015年第2期28卷 38-43页

作者： Carrera, Arnau Palomeras, Narcís Hurtós, Natàlia Carreras, Marc Computer Vision and Robotics Institute Centre d'Investigació en Robòtica Submarina Universitat de Girona Girona17003 Spain

Recent efforts in the field of intervention-autonomous underwater vehicles (I-AUVs) have started to show promising results in simple manipulation tasks. However, there is still a long way to go to reach the complexity of the tasks carried out by ROV pilots. This paper proposes an intervention framework based on Learning by Demonstration (LbD) techniques in order to easily acquire the manipulation skills of a pilot and be able to reproduce similar tasks autonomously. We describe the learning algorithm as well as its interplay with the rest of the modules (navigation, perception, control) that take part in the proposed framework. We show results on a free-floating valve turning task, using Girona 500 AUV equipped with a manipulator, a passive gripper, a force/torque sensor, a camera and a haptic device to perform the demonstrations. Obtained results show the feasibility of the LbD algorithm to perform autonomous intervention even under the presence of perturbations. © 2015, IF AG (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Autonomous underwater vehicles Demonstrations Learning algorithms Learning systems Remotely operated vehicles Autonomous interventions Autonomous underwater vehicles (AUV) Free floating manipulation Human Machine Interface Learning by demonstration

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Pose estimation for underwater vehicles using light beacons

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IFAC-PapersOnLine 2015年第2期28卷 70-75页

作者： Gracias, Nuno Bosch, Josep Karim, Mohammad Ehsanul Computer Vision and Robotics Institute Centre d'Investigació en Robòtica Submarina Universitat de Girona Girona17003 Spain

This paper presents an approach for estimating the relative location and orientation between two or more underwater vehicles operating in tight formation. One of the vehicles is equipped with a camera of wide field of view. The other vehicle(s) are equipped with active light markers to enable the use of computer vision for pose estimation. The pose estimation addresses two scenarios, which are both important from the operational point of view. The first pertains to the availability of an acoustic communication channel which allows for exchanging attitude data and acoustic ranging, and use it in the pose estimation procedure. The second corresponds to the exclusive use of a set of 4 or more optical beacons with no acoustic information exchange, which is a capability that has not been yet proposed nor demonstrated in underwater vehicles. The contributions can be summarize as (1) a novel method of estimating the pose of an autonomous underwater vehicle using light beacons and other sensors when available, (2) an automated marker configuration analysis approach. Performance of the pose estimation approach is evaluated using synthetic and real data. © 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Underwater acoustics Autonomous underwater vehicles computer vision Navigation Optical systems Visual servoing Active markers Cooperative navigations Formation control Relative localization Robot navigation Underwater vehicles

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Joint Design of Radar Receive Filter and Unimodular ISAC Waveform with Sidelobe Level Control

arXiv

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arXiv 2025年

作者： Zhang, Kecheng Liu, Ya-Feng Wang, Zhongbin Yuan, Weijie Keskin, Musa Furkan Wymeersch, Henk Xia, Shuqiang School of System Design and Intelligent Manufacturing The Shenzhen Key Laboratory of Robotics and Computer Vision Southern University of Science and Technology Shenzhen518055 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden ZTE Corporation The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China

Integrated sensing and communication (ISAC) has been considered a key feature of next-generation wireless networks. This paper investigates the joint design of the radar receive filter and dual-functional transmit waveform for the multiple-input multiple-output (MIMO) ISAC system. While optimizing the mean square error (MSE) of the radar receive spatial response and maximizing the achievable rate at the communication receiver, besides the constraints of full-power radar receiving filter and unimodular transmit sequence, we control the maximum range sidelobe level, which is often overlooked in existing ISAC waveform design literature, for better radar imaging performance. To solve the formulated optimization problem with convex and nonconvex constraints, we propose an inexact augmented Lagrangian method (ALM) algorithm. For each subproblem in the proposed inexact ALM algorithm, we custom-design a block successive upper-bound minimization (BSUM) scheme with closed-form solutions for all blocks of variable to enhance the computational efficiency. Convergence analysis shows that the proposed algorithm is guaranteed to provide a stationary and feasible solution. Extensive simulations are performed to investigate the impact of different system parameters on communication and radar imaging performance. Comparison with the existing works shows the superiority of the proposed algorithm. © 2025, CC BY-NC-SA.

关键词： Mean square error

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