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检索条件"任意字段=International Symposium on Computational Intelligence in Robotics and Automation"

共 3099 条记录，以下是331-340 订阅

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Task-Space Decomposed Motion Planning Framework for Multi-Robot Loco-Manipulation

Task-Space Decomposed Motion Planning Framework for Multi-Ro...

引用

IEEE international Conference on robotics and automation (ICRA)

作者： Zhang, Xiaoyu Yan, Lei Lam, Tin Lun Vijayakumar, Sethu Shenzhen Inst Artificial Intelligence & Robot Soc Shenzhen Peoples R China Univ Edinburgh Sch Informat Edinburgh Midlothian Scotland Chinese Univ Hong Kong Shenzhen Peoples R China Airs Shenzhen Peoples R China

ISBN: (纸本)9781728190778

This paper introduces a novel task-space decomposed motion planning framework km multi-robot simultaneous locomotion and manipulation. When several manipulators hold an object, closed-chain kinematic constraints are formed, and it will make the motion planning problems challenging by inducing lower-dimensional singularities. Unfortunately, the constrained manifold will he even more complicated when the manipulators are equipped with mobile bases. We address the problem by introducing a dual-resolution motion planning framework which utilizes a convex task region decomposition method, with each resolution tuned to efficient computation for their respective roles. Concretely, this dual-resolution approach enables a global planner to explore the low-dimensional decomposed task-space regions toward the goal, then a local planner computes a path in high-dimensional constrained configuration space. We demonstrate the proposed method in several simulations, where the robot team transports the object toward the goal in the obstacle-rich environments.

关键词： Manifolds Conferences computational modeling Kinematics System recovery Manipulators Planning

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Decentralized Connectivity Maintenance with Time Delays using Control Barrier Functions

Decentralized Connectivity Maintenance with Time Delays usin...

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IEEE international Conference on robotics and automation (ICRA)

作者： Capelli, Beatrice Fouad, Hassan Beltrame, Giovanni Sabattini, Lorenzo Univ Modena & Reggio Emilia Dept Sci & Methods Engn DISMI Modena Italy Ecole Polytech Montreal Dept Comp & Software Engn Montreal PQ Canada

ISBN: (纸本)9781728190778

Connectivity maintenance is crucial for the real world deployment of multi-robot systems, as it ultimately allows the robots to communicate, coordinate and perform tasks in a collaborative way. A connectivity maintenance controller must keep the multi-robot system connected independently from the system's mission and in the presence of undesired real world effects such as communication delays, model errors, and computational time delays, among others. In this paper we present the implementation, on a real robotic setup, of a connectivity maintenance control strategy based on Control Barrier Functions. During experimentation, we found that the presence of communication delays has a significant impact on the performance of the controlled system, with respect to the ideal case. We propose a heuristic to counteract the effects of communication delays, and we verify its efficacy both in simulation and with physical robot experiments.

关键词： Machine learning algorithms Robot kinematics Heuristic algorithms Delay effects computational modeling Maintenance engineering Delays

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AI Adoption in Healthcare: Addressing Challenges and Change Management

AI Adoption in Healthcare: Addressing Challenges and Change ...

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international symposium on computational intelligence and Informatics

作者： Vivien Leuba Noémi Piricz Innovation Management Doctoral School Óbuda University Budapest Hungary Keleti Károly Faculty of Business and Management Óbuda University Budapest Hungary

ISBN: (数字)9798350353433

ISBN: (纸本)9798350353440

The rapid advancement of Artificial intelligence (AI) presents new opportunities and challenges for companies, particularly in the areas of automation and innovation. However, the success of AI-technology implementation largely depends on effective change management, which aims to address employee resistance and also influences the organizational culture. This article highlights the importance of change management by examining its key success factors, the impact of leadership, and potential failure points, such as inadequate communication or insufficient resources. Furthermore, it explores the most effective models for AI technology implementation, with special focus on how change management practices facilitate successful integration. Additionally, the article explains the problems and challenges identified in the literature related to AI-adoption and change management, such as the lack of technological competencies, and ethical concerns surrounding new technologies. Finally, this paper proposes solutions that, when applied as strategies, can lead to successful implementation, including continuous education and training, clear goal setting and leadership commitment.

关键词： Resistance Training Technological innovation Leadership Ethics Navigation Companies Medical services Artificial intelligence Informatics

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Research on Propeller Blades Sanding Degree Recognition Algorithm Based on Improved DeepLabV3+ Network

Research on Propeller Blades Sanding Degree Recognition Algo...

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IEEE international Conference on Mechatronics, robotics and automation (ICMRA)

作者： Siying Cao Baocheng Yu Wenxia Xu College of Computer Science and Engineering College of Artificial Intelligence Wuhan Institute of Technology Wuhan China

ISBN: (数字)9798350352474

ISBN: (纸本)9798350352481

In the overhaul process of airplane propeller blades, the foam filling on the shoulder of the blades needs to be ground off. To achieve automated recognition of the sanding degree of propeller blades, an image semantic segmentation algorithm based on the improved DeepLabV3+ network is proposed. The algorithm adopts a lightweight network, MobileNetV2, to replace the original backbone network of DeepLabv3+, reducing computational complexity. The atrous spatial pyramid pooling (ASPP) feature extraction module is improved by replacing the atrous convolution with depthwise separable convolution and introducing the Convolutional Block Attention Module(CBAM), enhancing the overall training efficiency and segmentation accuracy of the model. Group normalization (GN) is used instead of batch normalization (BN) to further improve model performance. The experimental results on the dataset collected from the propeller blades sanding site show that the proposed algorithm achieves a mean intersection over union (MioU) of 91.40%, a mean pixel accuracy (MPA) of 95.63%, and an inference speed (FPS) of 33.88. Compared to the current mainstream segmentation algorithms such as DeepLabV3+, PSPNet, and HRNet, the improved algorithm demonstrates enhanced segmentation accuracy and inference speed.

关键词： Training Airplanes Accuracy Image recognition Propellers Convolution Blades Semantic segmentation Inference algorithms robotics and automation

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Autonomous Exploration Using a Tree Structure For Goal Selection

Autonomous Exploration Using a Tree Structure For Goal Selec...

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international symposium on Applied computational intelligence and Informatics ( SACI)

作者： Barbara Abonyi-Tóth Ákos Nagy Department of Automation and Applied Informatics Budapest University of Technology and Economics Budapest Hungary

Autonomous exploration of unknown environments using unmanned robots is a widely researched problem of our days. The focus of this paper is to provide a novel goal-selection method in response to the problems of the simple greedy goal selection algorithm. The presented method uses a tree structure built from the detected frontiers and selects the next goal of exploration using a depth-first search on the expanding tree. This prevents the exploring robot from leaving half-explored areas and backtracking to them later in the exploration. The method is tested in two simulated environments. The results are compared to those achieved using a simple greedy goal selection algorithm.

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Koopman NMPC: Koopman-based Learning and Nonlinear Model Predictive Control of Control-affine Systems

Koopman NMPC: Koopman-based Learning and Nonlinear Model Pre...

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IEEE international Conference on robotics and automation (ICRA)

作者： Folkestad, Carl Burdick, Joel W. CALTECH Div Engn & Appl Sci Pasadena CA 91125 USA

ISBN: (纸本)9781728190778

Koopman-based learning methods can potentially be practical and powerful tools for dynamical robotic systems. However, common methods to construct Koopman representations seek to learn lifted linear models that cannot capture nonlinear actuation effects inherent in many robotic systems. This paper presents a learning and control methodology that is a first step towards overcoming this limitation. Using the Koopman canonical transform, control-affine dynamics can be expressed by a lifted bilinear model. The learned model is used for nonlinear model predictive control (NMPC) design where the bilinear structure can be exploited to improve computational efficiency. The benefits for control-affine dynamics compared to existing Koopman-based methods are highlighted through an example of a simulated planar quadrotor. Prediction error is greatly reduced and closed loop performance similar to NMPC with full model knowledge is achieved.

关键词： Learning systems Dictionaries System dynamics computational modeling Transforms Predictive models Tools

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computational intelligence: A Broader Horizon

Computational Intelligence: A Broader Horizon

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IEEE international Conference on Research, Innovation and Vision for the Future

作者： Narayan C. Debnath Eastern International University Vietnam

ISBN: (数字)9798331505073

ISBN: (纸本)9798331505080

Current developments of intelligent software technology have been playing an important role in a broad range of innovative applications. Major industries such as automotive, telecommunications, banking, e-business, automation, and recent smart applications in artificial intelligence (AI), machine learning (ML), deep learning, robotics, internet of things and smart devices, smart environment and technology, and many others are highly dependent on intelligent computer software for their basic operations. Moreover, the integration of artificial intelligence with machine learning, deep learning, and block chain are proving to be quite a powerful combination for improving virtually every industry in which they are implemented. AI and ML applications to academics to automobiles to railways to Aviation to healthcare industries are helping to significantly improve reliability, services, safety, and protection to human life and lifestyle. This keynote presentation will address recent applications of intelligent software systems along with the future potential growth of AI. Fundamental concepts and limitations connected with the reliability of intelligent software systems will be introduced. Several issues of software validation techniques involved in maximizing the reliability of a large and complex intelligent software system will be explored. The discussion and presentation may help identify new and innovative research directions for further study and development in computational intelligence with wide range of emerging applications along with the challenges and opportunities.

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Hierarchical MCTS for Scalable Multi-Vessel Multi-Float Systems

Hierarchical MCTS for Scalable Multi-Vessel Multi-Float Syst...

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IEEE international Conference on robotics and automation (ICRA)

作者： D'urso, Giovanni Lee, James Ju Heon Pizarro, Oscar Yoo, Chanyeol Fitch, Robert Univ Technol Sydney Sydney NSW 2007 Australia Univ Sydney Australian Ctr Field Robot Sydney NSW 2006 Australia

ISBN: (纸本)9781728190778

Systems of multiple low-cost, underactuated floats combined with fully actuated surface vessels can improve the scalability and cost-effectiveness of autonomous systems for marine science and environmental monitoring. Here, we consider a coordination problem where surface vessels must drop off floats at locations such that they are likely to drift to observe given points of interest, and later must pick up the floats for redeployment. We define the Multi-Vessel Multi-Float (MVMF) problem and present a hierarchical solution based on the Dec-MCTS algorithm. Our solution defines customised sampling, rollout, and action generation algorithms to accommodate the problem's large search space and provide computational performance sufficient for practical application. We report analytical and simulation results that demonstrate the computational efficiency of our method and validate its behaviour in practical problems. These results immediately enable field experiments to progress the development of this exciting concept in multi-robot marine systems.

关键词： automation Autonomous systems Simulation Scalability Conferences Search problems Oceanography

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Performance Metrics Calculation for Assembly Systems with Exponential Reliability Machines

Performance Metrics Calculation for Assembly Systems with Ex...

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IEEE international Conference on robotics and automation (ICRA)

作者： Bai, Yishu Zhang, Liang

ISBN: (纸本)9781728190778

Assembly systems are commonly seen in production practice, where multiple components are joined in a manufacturing process to make a final product. In this paper, a decomposition/aggregation-based method is presented to evaluate the performance metrics of assembly systems with machines following the exponential reliability model (either synchronous or asynchronous). In particular, we consider the assembly system with multiple merge operations, each connected to a single external component line. The idea of the proposed method is to decompose the assembly system into a set of virtual serial lines based on the overlapping decomposition technique, evaluate of the starvation and blockage of the merge operations, and recursively update of the virtual machines' parameters in the thus-obtained serial lines. Then, the performance metrics of the original assembly system can be approximated based on the corresponding machines and buffers in the virtual serial lines. Numerical experiments are carried out to justify the convergence and computational efficiency of the method, as well as to evaluate the approximation accuracy of the proposed algorithm.

关键词： Measurement Assembly systems Software packages Software algorithms Approximation algorithms computational efficiency Steady-state

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Agile Actions with a Centaur-Type Humanoid: A Decoupled Approach

Agile Actions with a Centaur-Type Humanoid: A Decoupled Appr...

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IEEE international Conference on robotics and automation (ICRA)

作者： Polverini, Matteo Parigi Hoffman, Enrico Mingo Laurenzi, Arturo Tsagarakis, Nikos G. Ist Italiano Tecnol IIT Humanoids & Human Ctr Mechatron Res Line HHCM Genoa Italy

ISBN: (纸本)9781728190778

The kinematic features of a centaur-type humanoid platform, combined with a powerful actuation, enable the experimentation of a variety of agile and dynamic motions. However, the higher number of degrees-of-freedom and the increased weight of the system, compared to the bipedal and quadrupedal counterparts. pose significant research challenges in terms of computational load and real implementation. To this end, this work presents a control architecture to perform agile actions, conceived for torque-controlled platforms, which decouples for computational purposes offline optimal control planning of lower-body primitives, based on a template kinematic model, and online control of the upper-body motion to maintain balance. Three stabilizing strategies are presented, whose performance is compared in two types of simulated jumps, while experimental validation is performed on a half-squat jump using the CENTAURO robot.

关键词： automation Conferences Dynamics Humanoid robots Optimal control Kinematics Computer architecture

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