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检索条件"任意字段=18th International Conference on Control Automation Robotics and Vision"

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Data-driven Holistic Framework for Automated Laparoscope Optimal View control with Learning-based Depth Perception

Data-driven Holistic Framework for Automated Laparoscope Opt...

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IEEE international conference on robotics and automation (ICRA)

作者： Li, Bin Lu, Bo Lu, Yiang Dou, Qi Liu, Yun-Hui Chinese Univ Hong Kong Dept Mech & Automat Engn T Stone Robot Inst Hong Kong Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Peoples R China Chinese Univ Hong Kong T Stone Robot Inst Hong Kong Peoples R China

ISBN: (纸本)9781728190778

Laparoscopic Field of View (FOV) control is one of the most fundamental and important components in Minimally Invasive Surgery (MIS), nevertheless the traditional manual holding paradigm may easily bring fatigue to surgical assistants, and misunderstanding between surgeons also hinders assistants to provide a high-quality FOV. Targeting this problem, we here present a data-driven framework to realize an automated laparoscopic optimal FOV control. To achieve this goal, we offline learn a motion strategy of laparoscope relative to the surgeon's hand-held surgical tool from our in-house surgical videos, developing our control domain knowledge and an optimal view generator. To adjust the laparoscope online, we first adopt a learning-based method to segment the two-dimensional (2D) position of the surgical tool, and further leverage this outcome to obtain its scale-aware depth from dense depth estimation results calculated by our novel unsupervised RoboDepth model only with the monocular camera feedback, hence in return fusing the above real-time 3D position into our control loop. To eliminate the misorientation of FOV caused by Remote Center of Motion (RCM) constraints when moving the laparoscope, we propose a novel rotation constraint using an affine map to minimize the visual warping problem, and a null-space controller is also embedded into the framework to optimize all types of errors in a unified and decoupled manner. Experiments are conducted using Universal Robot (UR) and Karl Storz Laparoscope/Instruments, which prove the feasibility of our domain knowledge and learning enabled framework for automated camera control.

关键词： Laparoscopes Visualization Solid modeling three-dimensional displays Two dimensional displays Robot vision systems Tools

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Formation Tracking control with Adaptive Neural Networks Estimation 16

Formation Tracking Control with Adaptive Neural Networks Est...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Huang, Rong Chen, Yang-Yang Southeast Univ Sch Automat Nanjing 210096 Peoples R China

ISBN: (纸本)9781728177090

this paper takes the planar formation tracking control problem of second-order agents with model uncertainties into consideration. A novel adaptive neural network (ANN) estimation method based on neighborhood information is designed to estimate model uncertainties. By using the tools of the back-stepping method and ANN, a robust formation tracking control law is given. the law can guarantee this formation tracking errors uniformly bounded under connected topologies. Numerical simulation results verify the validity of the analysis results.

关键词： Uncertainty analysis

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Investigating the Performances of control Parameterizations for Nonlinear Model Predictive control

Investigating the Performances of Control Parameterizations ...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Franco Fusco Guillaume Allibert Olivier Kermorgant Philippe Martinet Université Côte d'Azur CNRS France Centrale Nantes Laboratoire des Sciences du Numérique de Nantes LS2N Nantes France Université Côte d'Azur INRIA Sophia-Antipolis France

ISBN: (纸本)9781665476881

Solving Direct Shooting Model Predictive control (MPC) optimization problems online can be computationally expensive if a large horizon is used while also maintaining a dense time sampling. In these cases, it is accepted that tradeoffs between computational load and performances should be sought in order to meet real-time feasibility requirements. However, making the problem more tractable for the hardware should not necessarily imply a decrease in performances. One technique that has been proposed in the literature makes use of control input parameterizations to decrease the numerical complexity of nonlinear MPC problems without necessarily affecting the performances significantly. In this paper, we review the use of parameterizations and propose a simple Sequential Quadratic Programming algorithm for nonlinear MPC. We then benchmark the performances of the solver in simulation, showing that parameterizations allow to attain good performances with (significantly) lower computation times than state-of-the-art solvers.

关键词： Software libraries Stability analysis Hardware Real-time systems Reliability Quadratic programming Optimization

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Motion primitives-based and Two-phase Motion Planning for Fixed-wing UAV

Motion primitives-based and Two-phase Motion Planning for Fi...

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international conference on control, automation, robotics and vision (ICARCV)

作者： Zheng Tan Yang Lyu Hanchen Lu Quan Pan Faculty of Automation Northwestern Polytechnical University Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781665476881

We present an efficient two-phase approach to motion planning for fixed-wing Unmanned Aerial Vehicles (UAV) navigating in complex 3D air slalom environments. Firstly, in discrete 3D workspace, a global planner computer a obstacle-free path roughly which satisfies the kinematic constraints of the UAV. Given a coarse global path, a local planner generate a Dubins curve with collision avoidance based on the UAS's perception constraints, dynamic constraints and the collision perception information received. We also introduce a method of decoupling the horizontal and vertical motion directions of the fixed-wing UAV, realizing the 2D Dubins curve planning in 3D workspace, along with precomputed sets of motion primitives derived from the vehicle dynamics model in order to achieve high efficiency. Finally, the feasibility of two-phase 3D motion planning in appropriate FOV is experimentally demonstrated.

关键词： Solid modeling three-dimensional displays Navigation Dynamics Organizations Kinematics Autonomous aerial vehicles

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Night vision Bot using Dynamic IR and Object Detection 5

Night Vision Bot using Dynamic IR and Object Detection

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5th international conference on Electrical, Electronics, Communication, Computer Technologies and Optimization Techniques (ICEECCOT)

作者： Abhyankar, Devesh Suresh, Gurumoorty Karjule, Hrithik Sambhaji Bhardwaj, Parth Muleva, Harish Mahajan, Anurag Symbiosis Int Deemed Univ SIU Symbiosis Inst Technol Dept OfElect & Telecommun Pune Maharashtra India Dell Technol Bangalore Karnataka India

ISBN: (纸本)9781665432726

robotics as an extension to the field of Engineering has been of great support to the evolution of mankind through robotics, even complex tasks can be simplified through simple automation and decreased human intervention. Robots even reduce the workload on humans and increase the level of efficiency and accuracy in doing any task. robotics has branched out and helped in the development and evolution of many fields such as agriculture, defense, parenting, healthcare, industry, aerospace and, so on. the robots which are used for survey or exploration can be used for many purposes in the fields of Wildlife, Industry and, Defense. these robots are capable of going to the areas which are vulnerable for humans, and they can be controlled from a reasonable distance. this robot due to its small size and inbuilt night vision camera makes it a very useful tool for surveillance and exploration. this robot has the ability to be controlled from a distance and it will enable the users to view objects clearly at night (or in darkness). these types of robots have been in existence for a couple of years, only for new developments to be added to them. the very recent development involves the integration of IoT (Internet of things) to control the robot remotely and obtain information from it. the latest addition however is the addition of a new concept, known as Dynamic IR, which involves the control of the intensity of the IR light to produce better images. Moreover, with the addition of Object Detection using Machine Learning Algorithms, it can predict what type of obstacle it may face.

关键词： Dynamic IR Night vision Object Detection Raspberry Pi

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Adaptive control for a Class of Uncertain Nonlinear Systems Subject to Saturated Input Quantization 16

Adaptive Control for a Class of Uncertain Nonlinear Systems ...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Xing, Lantao Wen, Changyun Liu, Zhitao Cai, Jianping Zhang, Meng

ISBN: (纸本)9781728177090

In this paper, we study the adaptive tracking control problem for a class of uncertain nonlinear systems with input quantization. Different from the existing results, we propose a new quantizer with saturated quantization levels motivated by the saturation property of practical actuators and sensors. With this new quantizer, we know the exact number and values of the quantization levels in advance, regardless of the magnitude of the designed control signal. thus, we only need to code these quantization levels accordingly such that less network resources are consumed. It is shown that the proposed control scheme guarantees that all the closed-loop signals are globally bounded and the tracking error converges towards a known compact set.

关键词： Nonlinear systems

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Path planning and reference tracking for a 18DoF quadruped robot

Path planning and reference tracking for a 18DoF quadruped r...

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international conference on System theory, control, and Computing (ICSTCC)

作者： Mihai V. Zaha Bogdan Muntean Sorin M. Grigorescu Department of Automation and Information Technology Robotics Vision and Control Laboratory (RovisLab) Transilvania University of Brasov Romania

Quadruped robots and many other types of legged robots have been gaining popularity in recent years due to their advantages over wheeled robots. Firstly, quadruped robots have excellent mobility and stability. With four legs, the quadruped robots can move more efficiently over rough terrain and uneven surfaces, making them a prime candidate for use in disaster response situations, search and rescue operations and exploration missions. Furthermore, quadruped robots don’t have holonomic constraints, thus making them more maneuverable than any other type of robots. this makes them ideal for use in confined spaces. the problem of quadruped control can be divided in low level and high level control, the former concerning each joint angle position, velocity, acceleration and torque to achieve a desired motion for each leg, while the latter is concerned with the required whole-body linear and angular velocities to follow a specified trajectory. In this paper we present a high level control strategy using Dynamic Window Approach (DWA) and a modified dynamic model for the quadruped’s whole-body dynamics. Furthermore, we study the effects of modified mass-inertia matrix on the overall performance of the algorithm. We conduct our experiments in a proprietary simulated environment and in real world.

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Application of CNN-Based Method for Automatic Detection and Classification of the IC Packages 16

Application of CNN-Based Method for Automatic Detection and ...

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16th IEEE international conference on control, automation, robotics and vision (ICARCV)

作者： Malinski, Kamil Marek Okarma, Krzysztof West Pomeranian Univ Technol Szczecin Fac Elect Engn Dept Signal Proc & Multimedia Engn PL-70313 Szczecin Poland

ISBN: (纸本)9781728177090

Automatic detection and classification of integrated circuits' packages is one of the methods supporting the traditional production of electronic parts based on through-hole technology, typical for Printed Circuit Boards (PCBs), utilizing the advantages of modern machine vision solutions. As a result of the growing availability of cameras and 3D printers, as well as the popularity of IoT systems, prototyping of some electronic circuits with the use of simpler robotic systems may be supported by an automatic analysis of electronic components based on machine vision. Considering recent advances in the applications of Convolutional Neural Networks (CNNs) in computer vision, their applicability for this task has been analyzed and experimentally verified in this paper, also in comparison to previously proposed approach based on handcrafted features.

关键词： Computer vision

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Visible-Infrared Cross-Modal Person Re-Identification Based on Modality Alignment and Fine-Grained Mining

Visible-Infrared Cross-Modal Person Re-Identification Based ...

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IEEE international conference on Cyber Technology in automation, control, and Intelligent Systems

作者： Yingchang Zhao Hang Yu Zhuxuan Cheng Huijie Fan Sen Lin School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China School of Information Engineering Shenyang University of Chemical Technology Shenyang China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

In the current field of computer vision, visible-infrared cross-modal person re-identification has become a research topic of great interest. this task aims to identify and match images of the same pedestrian from different modalities and is widely applied in scenarios like night-time surveillance and multi-camera tracking. However, due to significant visual differences between modalities, this task faces many challenges. To overcome these challenges, in this paper we propose a cross-modal person re-identification method based on modality alignment and fine-grained local feature mining. First, we introduce the Modality Alignment Module, which aims to reduce visual differences between modalities, thereby providing a more consistent foundation for feature extraction and matching. then, through the Fine-grained Mining Module, we delve into the local details in pedestrian images to enhance the distinctiveness of features and the accuracy of identification. Moreover, by incorporating advanced deep learning architectures and optimization algorithms, our method shows exceptional results on both SYSU-MM01 and RegDB datasets.

关键词： Visualization Pedestrians Surveillance Deep architecture Feature extraction Robustness Intelligent systems Optimization Faces Identification of persons

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KI-Net: AI-Based Optimization in Industrial Manufacturing—A Project Overview 18th

KI-Net: AI-Based Optimization in Industrial Manufacturing—...

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18th international conference on Computer Aided Systems theory, EUROCAST 2022

作者： Freudenthaler, Bernhard Martinez-Gil, Jorge Fensel, Anna Höfig, Kai Huber, Stefan Jacob, Dirk Software Competence Center Hagenberg GmbH Softwarepark 32a Hagenberg4232 Austria Innsbruck University of Innsbruck Technikerstraße 21a Innsbruck6020 Austria Rosenheim Technical University of Applied Sciences Hochschulstraße 1 Rosenheim83024 Germany Salzburg University of Applied Sciences Urstein Süd 1 Puch/Salzburg5412 Austria University of Applied Sciences Kempten Bahnhofstraße 61 Kempten87435 Germany

ISBN: (纸本)9783031253119

Artificial intelligence (AI) is a crucial technology of industrial digitalization. Especially in the production industry, a great potential is present in optimizing existing processes, e.g., concerning resource consumption, emission reduction, process and product quality improvements, predictive maintenance, and so on. Some of this potential is addressed by methods of industrial analytics beyond specific production technology. Furthermore, particular technological aspects in production systems address another part of this potential, e.g., mechatronics, robotics and motion control, automation systems, and so on. the problem is that the field of AI includes many research areas and methods, and many companies are losing the overview of the necessary and appropriate methods for solving the company problems. the reasons for this are, on the one hand, a lack of expertise in AI and, on the other hand, high complexity and risks of use for the companies (especially for SMEs). As a result, many potentials cannot yet be exploited. the KI-NET project aims to fill this gap, whereby a project overview is presented in this contribution. © 2022, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： robotics

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