检索结果-内蒙古大学图书馆

Saccadic predictive vision model with a fovea 18

学校读者我要写书评

暂无评论

Saccadic predictive vision model with a fovea

2018 International Conference on Neuromorphic systems, ICONS 2018

作者： Hazoglou, Michael Hylton, Todd Contextual Robotics Institute University of California San Diego San DiegoCA United States Department of Electrical and Computer Engineering University of California San Diego San DiegoCA United States

ISBN: (纸本)9781450365444

We propose a model that emulates saccades, the rapid movements of the eye, called the Error Saccade Model, based on the prediction error of the Predictive Vision Model (PVM). The Error Saccade Model carries out movements of the model's field of view to regions with the highest prediction error. Comparisons of the Error Saccade Model on Predictive Vision Models with and without a fovea show that a fovea-like structure in the input level of the PVMimproves the Error Saccade Model's ability to pursue detailed objects in its view. We hypothesize that the improvement is due to poorer resolution in the periphery causing higher prediction error when an object passes, triggering a saccade to the next location. © 2018 Association for Computing Machinery.

关键词： Eye movements

An Adaptive Strategy via Reinforcement Learning for the Prisoner＇s Dilemma Game

学校读者我要写书评

暂无评论

IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 301-310页

作者： Lei Xue Changyin Sun Donald Wunsch Yingjiang Zhou Fang Yu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing 210096 China Department of Electrical and Computer Engineering Missouri University of Science and Technology Rolla MO 65409 USA College of Automation Nanjing University of Posts and Telecommunications Nanjing 210023 China Institute of Logistics Science and Engineering Shanghai Maritime University Shanghai 210096 China IEEE

The iterated prisoner's dilemma(IPD) is an ideal model for analyzing interactions between agents in complex networks. It has attracted wide interest in the development of novel strategies since the success of tit-for-tat in Axelrod's tournament. This paper studies a new adaptive strategy of IPD in different complex networks, where agents can learn and adapt their strategies through reinforcement learning method. A temporal difference learning method is applied for designing the adaptive strategy to optimize the decision making process of the agents. Previous studies indicated that mutual cooperation is hard to emerge in the IPD. Therefore, three examples which based on square lattice network and scale-free network are provided to show two features of the adaptive strategy. First, the mutual cooperation can be achieved by the group with adaptive agents under scale-free network, and once evolution has converged mutual cooperation, it is unlikely to shift. Secondly, the adaptive strategy can earn a better payoff compared with other strategies in the square network. The analytical properties are discussed for verifying evolutionary stability of the adaptive strategy.

关键词： Complex network prisoner’s dilemma reinforcement learning temporal differences learning

Anisotropic flocking control of distributed multi-agent systems using fluid abstraction

学校读者我要写书评

暂无评论

Anisotropic flocking control of distributed multi-agent syst...

AIAA Information systems-AIAA Infotech at Aerospace, 2018

作者： Silic, Matthew Song, Zhuoyuan Mohseni, Kamran Department of Mechanical and Aerospace Engineering University of Florida GainesvilleFL32611 United States Electrical and Computer Engineering Department Institute for Networked Autonomous Systems University of Florida GainesvilleFL32611 United States

ISBN: (数字)9781624105272

ISBN: (纸本)9781624105272

This paper presents a multi-agent flocking scheme for real-time control of homogeneous unmanned aerial vehicles (UAVs) based on smoothed particle hydrodynamics. Swarm cohesion, collision avoidance, and velocity consensus are concurrently satisfied by characterizing the emerging macroscopic flock as a continuous fluid. Two vital implementation issues are addressed in particular including latency in information fusion and directionality of communication due to antenna patterns. Symmetric control forces are achieved by meticulous scheduling of inter-vehicle communication to sustain the motion stability of the flock. A generalized, anisotropic smoothing kernel that takes into account the relative position and attitude between agents is adopted to address potential flocking instability introduced by communication anisotropy due to the antenna radiation pattern. The feasibility of the technique is demonstrated experimentally using a single UAV avoiding a virtual obstacle. © 2018, American institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Directional patterns (antenna)

Motion planning for multi-mobile-manipulator payload transport systems

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Tallamraju, Rahul Salunkhe, Durgesh Haribhau Rajappa, Sujit Ahmad, Aamir Karlapalem, Kamalakar Shah, Suril Vijaykumar Agents and Applied Robotics Group IIIT Hyderabad India Dibris Department University of Genoa Italy Department of Computer Science University of Tübingen Germany Max Planck Institute for Intelligent Systems Tübingen Germany Mechanical Engineering Department IIT Jodhpur India

In this paper, a kinematic motion planning algorithm for cooperative spatial payload manipulation is presented. A hierarchical approach is introduced to compute realtime collision-free motion plans for a formation of mobile manipulator robots. Initially, collision-free configurations of a deformable 2-D virtual bounding box are identified, over a planning horizon, to define a convex workspace for the entire system. Then, 3-D payload configurations whose projections lie within the defined convex workspace are computed. Finally, a convex decentralized model-predictive controller is formulated to plan collision-free trajectories for the formation of mobile manipulators. This approach facilitates real-time motion planning for the system and is scalable in the number of robots. The algorithm is validated in simulated dynamic environments. Copyright © 2019, The Authors. All rights reserved.

关键词： Motion planning

Robustness of DNA Strand Displacement systems⋆⁎

学校读者我要写书评

暂无评论

IFAC-PapersOnLine 2018年第33期51卷 32-37页

作者： Nakakuki, Takashi Imura, Jun-ichi Kawamata, Ibuki Murata, Satoshi Department of Systems Design and Informatics School of Computer Science and Systems Engineering Kyushu Institute of Technology 680-4 Kawazu IizukaFukuoka820-8502 Japan Department of Mechanical and Environmental Informatics Tokyo Institute of Technology 2-12-1-W8-1 O-okayama Meguro-ku Tokyo152-8552 Japan Department of Robotics Graduate School of Engineering Tohoku University 6-6-1 Aoba Aramaki-Aza Aoba-Ward SendaiMiyagi980-8579 Japan

How to construct a reliable deoxyribonucleic acid (DNA) circuit is one of the most important issues in the field of molecular programming and computing. Such a circuit frequently suffers from various kinds of unintended binding reactions on account of a lower specificity of the molecular interaction emerging from base complementarity between DNA strands, which results in low reliability of the molecular circuit. In this study, we propose a method to quantitatively evaluate the robustness of a DNA circuit created by DNA strand displacement reactions. The highlight of our method is representing the circuit system contaminated by unintended reactions by a standard form of a disturbed nonlinear system and evaluating the robustness with the L2 gain by solving the Hamilton–Jacobi inequality. © 2018

关键词： Nucleic acids Differential equations DNA Electric network analysis Large scale systems Nonlinear equations Substitution reactions Binding reactions Circuit systems Dna strand displacements DNA strands Molecular circuits Molecular programming Nonlinear circuit Uncertainty

Concurrent Flow-Based Localization and Mapping in Time-Invariant Flow Fields*

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Song, Zhuoyuan Mohseni, Kamran Department of Mechanical and Aerospace Engineering University of Florida Department of Mechanical Engineering University of Hawai‘i at Mānoa HonoluluHI96822 United States Department of Mechanical and Aerospace Engineering Department of Electrical and Computer Engineering Institute for Networked Autonomous Systems University of Florida GainesvilleFL32611 United States

We present the concept of concurrent flow-based localization and mapping (FLAM) for autonomous field robots navigating within background flows. Different from the classical simultaneous localization and mapping (SLAM) problem, where the robot interacts with discrete features, FLAM utilizes the continuous flow fields as navigation references for mobile robots and provides flow field mapping capability with in-situ flow velocity observations. This approach is of importance to underwater vehicles in mid-depth oceans or aerial vehicles in GPS-denied atmospheric circulations. This article introduces the formulation of FLAM as a full SLAM solution motivated by the feature-based GraphSLAM framework. The performance of FLAM was demonstrated through simulation within artificial flow fields that represent typical geophysical circulation phenomena: a steady single-gyre flow field and a double-gyre flow field with unsteady turbulent perturbations. The results indicate that FLAM provides significant improvements in the robots’ localization accuracy and a consistent approximation of the background flow field. It is also shown that FLAM leads to smooth robot trajectory estimates. Copyright © 2019, The Authors. All rights reserved.

关键词： Flow fields

A strategic review on sustainable approaches in municipal solid waste management andenergy recovery: Role of artificial intelligence,economic stability andlife cycle assessment

学校读者我要写书评

暂无评论

Bioresource technology 2023年第1期379卷 129044页

作者： Rajendiran Naveenkumar Jayaraj Iyyappan Ravichandran Pravin Seifedine Kadry Jeehoon Han Raveendran Sindhu Mukesh Kumar Awasthi Samuel Lalthazuala Rokhum Gurunathan Baskar Biological Systems Engineering University of Wisconsin-Madison Madison WI 53706 United States Forest Products Laboratory USDA Forest Service Madison WI 53726 United States. Department of Biotechnology Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Thandalam Chennai 602107 India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119. India. Department of Applied Data Science Noroff University College Kristiansand Norway Artificial Intelligence Research Center (AIRC) Ajman University Ajman 346 United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon. Department of Chemical Engineering Pohang University of Science and Technology Pohang 37673 Republic of Korea. Department of Food Technology TKM Institute of Technology Kollam Kerala India. College of Natural Resources and Environment Northwest A&F University Yangling Shaanxi Province 712100 China. Department of Chemistry National Institute of Technology Silchar 788010 Assam India. Department of Biotechnology St. Joseph's College of Engineering Chennai 600119. India Department of Applied Data Science Noroff University College Kristiansand Norway. Electronic address: basg2002@***.

The consumption of energy levels has increased in association with economic growth and concurrently increased the energy demand from renewable sources. The need under Sustainable Development Goals (SDG) intends to explore various technological advancements for the utilization of waste to energy. Municipal Solid Waste (MSW) has been reported as constructive feedstock to produce biofuels, biofuel carriers and biochemicals using energy-efficient technologies in risk freeways. The present review contemplates risk assessment and challenges in sorting and transportation of MSW and different aspects of conversion of MSW into energy are critically analysed. The circular bioeconomy of energy production strategies and management of waste are also analysed. The current scenario on MSW and its impacts on the environment are elucidated in conjunction with various policies and amendments equipped for the competent management of MSW in order to fabricate a sustained environment.

关键词： Circular bioeconomy Municipal Solid Waste Risk assessment Sustainable Waste Management

Granular Computing: An Augmented Scheme of Degranulation Through a Modified Partition Matrix

学校读者我要写书评

暂无评论

arXiv 2020年

作者： Xu, Kaijie Pedrycz, Witold Li, Zhiwu Xing, Mengdao School of Electro-Mechanical Engineering Xidian University Xi’an710071 China Department of remote sensing science and technology School of Electronic Engineering Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Institute of Systems Engineering Macau University of Science and Technology Macau999078 China National Laboratory of Radar Signal Processing Xidian University Xi’an710071 China Collaborative Innovation Center of Information Sensing and Understanding Xidian University Xi’an710071 China National Key Laboratory of Microwave Imaging Technology Institute of Electronics Chinese Academy of Sciences Beijing100190 China

As an important technology in artificial intelligence Granular Computing (GrC) has emerged as a new multi-disciplinary paradigm and received much attention in recent years. Information granules forming an abstract and efficient characterization of large volumes of numeric data have been considered as the fundamental constructs of GrC. By generating centroids (prototypes) and partition matrix, fuzzy clustering is a commonly encountered way of information granulation. As a reverse process of granulation, degranulation involves data reconstruction completed on a basis of the granular representatives (decoding information granules into numeric data). Previous studies have shown that there is a relationship between the reconstruction error and the performance of the granulation process. Typically, the lower the degranulation error is, the better performance of granulation process becomes. However, the existing methods of degranulation usually cannot restore the original numeric data, which is one of the important reasons behind the occurrence of the reconstruction error. To enhance the quality of reconstruction (degranulation), in this study, we develop an augmented scheme through modifying the partition matrix. By proposing the augmented scheme, we dwell on a novel collection of granulation-degranulation mechanisms. In the constructed approach, the prototypes can be expressed as the product of the dataset matrix and the partition matrix. Then, in the degranulation process, the reconstructed numeric data can be decomposed into the product of the partition matrix and the matrix of prototypes. Both the granulation and degranulation are regarded as generalized rotation between the data subspace and the prototype subspace with the partition matrix and the fuzzification factor. By modifying the partition matrix, the new partition matrix is constructed through a series of matrix operations. We offer a thorough analysis of the developed scheme. Copyright © 2020, The Authors. Al

关键词： Granulation

Multi modal semantic segmentation using synthetic data

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Srivastava, Kartik Singh, Akash Kumar Hegde, Guruprasad M. Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani. Hyderabad India Department of Electrical Engineering Indian Institute of Technology Kanpur. Kanpur India Robert Bosch Research and Technology Center Bangalore India

Semantic understanding of scenes in threedimensional space (3D) is a quintessential part of robotics oriented applications such as autonomous driving as it provides geometric cues such as size, orientation and true distance of separation to objects which are crucial for taking mission critical decisions. As a first step, in this work we investigate the possibility of semantically classifying different parts of a given scene in 3D by learning the underlying geometric context in addition to the texture cues BUT in the absence of labelled real-world datasets. To this end we generate a large number of synthetic scenes, their pixel-wise labels and corresponding 3D representations using CARLA software framework. We then build a deep neural network that learns underlying category specific 3D representation and texture cues from color information of the rendered synthetic scenes. Further on we apply the learned model on different real world datasets to evaluate its performance. Our preliminary investigation of results show that the neural network is able to learn the geometric context from synthetic scenes and effectively apply this knowledge to classify each point of a 3D representation of a scene in real-world. Copyright © 2019, The Authors. All rights reserved.

关键词： Autonomous vehicles