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

共 3096 条记录，以下是71-80 订阅

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Mixture of Experts Based Scenario Prediction for Motion Forecasting

Mixture of Experts Based Scenario Prediction for Motion Fo...

引用

11th international symposium on computational intelligence and Industrial Applications, ISCIIA 2024

作者： Jia, Zongwei Ye, Peijun State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9789819647552

Vehicle motion prediction is of great significance in human-machine shared driving, as it is a basis for the virtual driver to make suitable driving strategies so as to better assist the human driver or even complete its own autonomous driving. While recent studies have achieved good results by applying an intention prediction module into the multi-modal trajectory generation strategy, they mostly give supervision between intention proposals and final predicted points with insufficient alignment method. This leads to a relatively low accuracy of the vehicle motion prediction. To tackle this challenge, we propose a graph-based model with mixture of experts (MOE) based intention prediction module, introducing an efficient scenario-based intention prediction mechanism to improve the performance of intention prediction task. Several testing was conducted on the Argoverse motion forecasting dataset, which showed that our model excels in predicting trajectories for multiple agents. And the ablation experiments have verified the efficency of our method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Deep learning

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Research on Sensor Fault Diagnosis Method Based on KPCA-AE Algorithm

Research on Sensor Fault Diagnosis Method Based on KPCA-AE A...

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11th international symposium on computational intelligence and Industrial Applications, ISCIIA 2024

作者： Fan, Jiongwei Zhang, Jia School of Automation Beijing Institute of Technology Beijing China National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789819647552

Sensors occupy a pivotal role in indoor fire detection, and any malfunction within their operation can potentially escalate into severe accidents. Multi-sensor networks utilized in indoor fire early warning systems are inherently characterized by their high dimensionality and intricate linear interdependencies, presenting substantial operational complexities. To address these complexities, the paper introduces a fault diagnosis method based on Kernel Principal Component Analysis combined with Autoencoders (KPCA-AE). This methodology harmoniously integrates KPCA and AE, where KPCA is utilized to reduce the dimensionality of the data, thereby facilitating the training of the AE model. The proposed method adeptly and precisely identifies faults based on reconstruction errors, introducing a novel and effective paradigm for fault diagnosis in indoor fire sensors. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Principal component analysis

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Multi-Agent Systems for Autonomous IoT Network Management Using Distributed Reinforcement Learning

Multi-Agent Systems for Autonomous IoT Network Management Us...

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international symposium on Advanced Computing and Communication (ISACC)

作者： Neelamegam G Rajaram Venkatesan Ramya SR R.S. Ramya Akshya. J M. Sundarrajan Mani Deepak Choudhry Department of Computer Science and Engineering VSB College of Engineering and Technology Coimbatore Tamil Nadu India Department of Artificial Intelligence and Data Science Builders Engineering College Tirupur Tamil Nadu India Department of Computer Science and Engineering Dr NGP Institute of Technology Coimbatore Tamil Nadu India Department of Computer Science and Engineering Sri Ramakrishna Engineering College Coimbatore Tamil Nadu India Department of Computational Intelligence SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Networking and Communications SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Computing Technologies SRM Institute of Science and Technology Chennai Tamil Nadu India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

The ever-growing complexity of IoT networks ignited by their wide scale adoption in applications such as smart cities, the industrial automation, and health care, compelled to develop sophisticated yet resource efficient and scalable network management solution. Centralized systems are traditional in architecture, which leads to higher latency and bottlenecks, while decentralized systems can distribute workloads however the lack of adaptability to real time, along with the difficulty of extracting maximum resource usage, are limitations. In recent years, reinforcement learning (RL) based approaches have taken shape as a promising alternative to facilitate the automated learning and optimisation of task management. However, there are two challenges for existing RL based methods: slow convergence, inefficient priority assignment of tasks, and poor coordination amongst agents in the case of dynamic, large scale IoT environment. To solve these challenges, in this research we propose a distributed reinforcement learning based multi agent framework for managing IoT network. The framework also integrates a task prioritization mechanism to dynamically choose an optimal task allocation solution. Further validation was performed in a simulated IoT environment where real world inspired datasets were used. The proposed framework demonstrated 30% more task throughput than centralized, 25% less latency than decentralized, and 40% more energy efficiency than current RL based systems. The system was further validated using advanced visualizations such as anomaly detection maps and resource allocation efficiency graphs, demonstrating its capacity to manage dynamic load of tasks and resource allocation. The proposed framework addresses the critical limitations of current methods, through scalable, adaptive, and energy efficient framework for managing IoT network, and accordingly helps advancing the intelligent and autonomous IoT systems.

关键词： Smart cities Reinforcement learning Medical services Throughput Dynamic scheduling Energy efficiency Real-time systems Resource management Optimization Multi-agent systems

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computational intelligence for high-precision industrial robots

Computational intelligence for high-precision industrial rob...

引用

2005 IEEE international symposium on computational intelligence in robotics and automation CIRA 2005

作者： Moberg, Stig ABB Automation Technologies - Robotics Sweden Motion Control Group ABB Robotics Västerås Department of Automatic Control Linköpings University

ABB has launched its fifth generation robot controller, the IRC5. The basic motion control of the IRC5 controller includes the TrueMove and QuickMove functionality for best possible production rate and quality. In addition to this, the MultiMove function enables new production concepts and more cost-effective solutions. To penetrate new market segments, ease-of-use, high precision and cost-effectiveness are important factors. The availability of low-cost computational power and, in some cases, sensor integration enables the use of cost-effective industrial robots for high-precision tasks.

关键词： Artificial intelligence

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intelligence computing for direct human-robot communication using natural language and cognitive graphics

Intelligence computing for direct human-robot communication ...

引用

1997 IEEE international symposium on computational intelligence in robotics and automation (CIRA 97) - Towards New computational Principles for robotics and automation

作者： Litvintseva, LV Tanaka, T Yamafuji, K Ulyanov, VS Univ of Electro-Communications Tokyo Japan

ISBN: (纸本)0818681381

Direct human-robot communication system based on natural language (NL) and cognitive graphics (CG) as a part of a new hierarchical structure of AI control system of mobile robot for service use (MRSU) is developed, The software of simulation system for direct human-robot communication and MRSU behavior based on NL and CG is described. The NL an CG is used for description and representation of possible external worlds in the robot artificial life, This system allows us to evaluate the control algorithms of real time robot behavior and to reduce difficulties connected with such troubles as robot collisions with real objects and robot hardware damages. The mathematical background of direct NL human-robot communication and robot behavior simulation system is knowledge engineering based on spatio-temporal and action logics, default reasoning, cognitive graphics and soft computing, The main concepts, structure, conceptual model of simulation system for description of artificial life of MRSU are discussed, The example of simulation and real experimental results are described.

关键词： Intelligent control

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computational intelligence techniques for multiuser detection of DS/CDMA signals

Computational intelligence techniques for multiuser detectio...

引用

IEEE international symposium on computational intelligence in robotics and automation

作者： Shayesteh, MG Menhaj, M Amindavar, H Urmia Univ Dept Elect Engn Orumiyeh Iran

ISBN: (纸本)0780378660

Multiple access interference and near-far effect cause the performance of the conventional single user detector in DS/CDMA systems to degrade. Due to high complexity of the optimum multiuser detector, suboptimal multiuser detectors with less complexity and reasonable performance have received considerable attention. In this paper we apply computational intelligence techniques including proposed modified genetic algorithm and our analysis of multilayer perceptron neural network for multiuser detection of DS/CDMA signals. We compare their performance from different points of view such as computational complexity, implementation and error rate. We also compare their performance with the other detectors used in CDMA.

关键词： Multiuser detection

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Evaluation of a parallel architecture and algorithm for mapping and localization

Evaluation of a parallel architecture and algorithm for mapp...

引用

international symposium on computational intelligence in robotics and automation

作者： Lyons, Damian M. Isner, Giselle R. Fordham Univ Dept Comp & Informat Sci Robot & Comp Vis Lab 340 JMH Bronx NY 10458 USA Fordham Univ Comp & Informat Sci Dept 340 JMH Bronx NY 10458 USA

ISBN: (纸本)9781424407897

The Beowulf cluster approach to parallel computation offers a potentially cheap and robust source of computational power for high complexity algorithms in robotics. The challenge is to integrate this approach with the mobility and time critical response constraints of many robotic algorithms. The key contributions of this paper are: (1) introduction of a computational architecture for integrating a cluster into the control architecture of one or more robots, (2) a cluster implementation of Thrun et al's Concurrent Localization and Mapping (CML) algorithm, and (3) presentation of results to illustrate the performance of the implemented CML algorithm and validate the architectural approach.

关键词： computational methods

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Solving the Stochastic Resource Allocation Problem Through an Adaptive Variable Neighborhood Search Algorithm

Solving the Stochastic Resource Allocation Problem Through ...

引用

11th international symposium on computational intelligence and Industrial Applications, ISCIIA 2024

作者： Ma, Weijie Wang, Heng Zhang, Jingyu Wang, Yujue Yu, Rui School of Automation Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789819647552

This study investigates the stochastic resource allocation (SRA) problem, commonly found in complex systems, where the success rates of resources completing tasks are described probabilistically. An adaptive variable neighborhood search (AVNS) algorithm is proposed to address the SRA problem, featuring a permutation encoding method based on pseudo-resources and pseudo-tasks. The AVNS algorithm employs multiple permutation-based operators in its shaking and intensification phases, regulated by an adaptive mechanism to determine the sequence of operator selection. Additionally, a marginal benefit-based constructive algorithm is utilized for initializing the AVNS’s initial solution. To validate the effectiveness of the proposed AVNS, we designed 24 test cases with varying distributions of task values and resource success probabilities, and analyzed the optimality gaps of different algorithms. The computational experiments demonstrate that the AVNS algorithm provides superior allocation schemes compared to existing algorithms in most instances, highlighting its robustness and efficiency in solving complex SRA problems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Normal distribution

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Teacher's load and timing of teaching based on interactive evolutionary robotics

Teacher's load and timing of teaching based on interactive e...

引用

IEEE international symposium on computational intelligence in robotics and automation

作者： Katagami, D Yamada, S Tokyo Inst Technol CISS IGSSE Tokyo 152 Japan

ISBN: (纸本)0780378660

We have proposed a fast learning method that enables a mobile robot to acquires autonomous behaviors from interaction between human and robot. In this research we develop a behavior learning method ICS (Interactive Classifier System) using interactive evolutionary computation considering an operator's teaching cost. As a result, a mobile robot is able to quickly learn rules by directly teaching from an operator. ICS is a novel evolutionary robotics approach using classifier system. In this paper, we investigate teacher's physical and mental load and proposed a teaching method based on timing of instruction using ICS.

关键词： Teaching

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Hardware objects of the circuits for robotics

Hardware objects of the circuits for robotics

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IEEE international symposium on computational intelligence in robotics and automation

作者： Sekine, M Kanamaru, T Kudoh, K Imanaka, H Shiga, Y Ito, H Myokan, Y Tokyo Univ Agr & Technol Fuchu Tokyo 183 Japan

ISBN: (纸本)0780378660

A hardware object is a capsule of circuits loaded into reconfigurable devices. It is dynamically constructed while an application run. Its driver is temporarily mounted on a real driver for a hardware module. The circuits axe suitable to preprocessing and postprocessing of robot systems. A commercial C++ compiler becomes an integrated design environment only attaching hardware object components and hardware object libraries.

关键词： Timing circuits

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