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检索条件"主题词=Algorithm design and analysis"

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A 3-D Bio-inspired Odor Source Localization and its Validation in Realistic Environmental Conditions

A 3-D Bio-inspired Odor Source Localization and its Validati...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Rahbar, Faezeh Marjovi, Ali Kibleur, Pierre Martinoli, Alcherio Ecole Polytech Fed Lausanne Distributed Intelligent Syst & Algorithms Lab Sch Architecture Civil & Environm Engn CH-1015 Lausanne Switzerland

ISBN: (纸本)9781538626825

Finding the source of gaseous compounds released in the air with robots finds several applications in various critical situations, such as search and rescue. While the distribution of gas in the air is inherently a 3D phenomenon, most of the previous works have downgraded the problem into 2D search, using only ground robots. In this paper, we have designed a bio-inspired 3D algorithm involving cross-wind Levy Walk, spiralling and upwind surge. The algorithm has been validated using high-fidelity simulations, and evaluated in a wind tunnel which represents a realistic controlled environment, under different conditions in terms of wind speed, source release rates and odor threshold. Studying success rate and execution time, the results show that the proposed method outperforms its 2D counterpart and is robust to the various setup conditions, especially to the source release rate and the odor threshold.

关键词： Three-dimensional displays Robot sensing systems Two dimensional displays algorithm design and analysis Search problems Surges

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Automated Driving by Monocular Camera Using Deep Mixture of Experts 28

Automated Driving by Monocular Camera Using Deep Mixture of ...

引用

28th IEEE Intelligent Vehicles Symposium (IV)

作者： John, V. Mita, S. Tehrani, H. Ishimaru, K. Toyota Technol Inst Nagoya Aichi Japan Denso Kariya Aichi Japan Nippon Soken Nishio Japan

ISBN: (纸本)9781509048045

In this paper, we propose a real-time vision-based filtering algorithm for steering angle estimation in autonomous driving. A novel scene-based particle filtering algorithm is used to estimate and track the steering angle using images obtained from a monocular camera. Highly accurate proposal distributions and likelihood are modeled for the second order particle filter, at the scene-level, using deep learning. For every road scene, an individual proposal distribution and likelihood model is learnt for the corresponding particle filter. The proposal distribution is modeled using a novel long short term memory network-mixture-of-expert-based regression framework. To facilitate the learning of highly accurate proposal distributions, each road scene is partitioned into straight driving, left turning and right turning sub-partitions. Subsequently, each expert in the regression framework accurately model the expert driver's behavior within a specific partition of the given road scene. Owing to the accuracy of the modelled proposal distributions, the steering angle is robustly tracked, even with a limited number of sampled particles. The sampled particles are assigned importance weights using a deep learning-based likelihood. The likelihood is modeled with a convolutional neural network and extra trees-based regression framework, which predicts the steering angle for a given image. We validate our proposed algorithm using multiple sequences. We perform a detailed parameter analysis and a comparative analysis of our proposed algorithm with different baseline algorithms. Experimental results show that the proposed algorithm can robustly track the steering angles with few particles in real-time even for challenging scenes.

关键词： Proposals Roads Prediction algorithms Turning Neural networks algorithm design and analysis Markov processes

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An Effort Bias for Sampling-based Motion Planning

An Effort Bias for Sampling-based Motion Planning

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) / Workshop on Machine Learning Methods for High-Level Cognitive Capabilities in Robotics

作者： Kiesel, Scott Gu, Tianyi Ruml, Wheeler Univ New Hampshire Dept Comp Sci Durham NH 03824 USA

ISBN: (纸本)9781538626825

Recent advances in sampling-based motion planning have exploited concepts similar to those used in the heuristic graph search community, such as computing heuristic cost-to-go estimates and using state-space abstractions to derive them. Following this trend, we explore how the concept of search effort can be exploited to find plans quickly. Most previous work in motion planning attempts to find plans quickly by preferring states with low cost-to-go. Recent work in graph search suggests that following search effort-to-go estimates can yield faster planning. In this paper, we demonstrate how this idea can be adapted to the context of kinodynamic motion planning. Our planner, BEAST, uses estimates of effort that are learned on-line to guide the expansion of a motion tree toward states through which a plan is estimated to be easy to find. We present results with four different simulated vehicles (car, hovercraft, blimp and quadrotor) in six different environments indicating that BEAST is able to find solutions much more quickly and has a higher success rate than previous methods. We see this work as further strengthening the algorithmic connections between motion planning and heuristic graph search.

关键词： Planning Vegetation Concrete Heuristic algorithms algorithm design and analysis Space exploration Trajectory

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2D SLAM Quality Evaluation Methods 21

2D SLAM Quality Evaluation Methods

引用

21st Conference of Open-Innovations-Association (FRUCT)

作者： Filatov, Anton Filatov, Artyom Krinkin, Kirill Chen, Baian Molodan, Diana St Petersburg Electrotech Univ LETI St Petersburg Russia MIT Cambridge MA 02139 USA

ISBN: (纸本)9789526865324

SLAM (Simultaneous Localization and mapping) is one of the most challenging problems for mobile platforms and there is a huge amount of modern SLAM algorithms. The choice of the algorithm that might be used in every particular problem requires prior knowledge about advantages and disadvantages of each algorithm. This paper presents the approach for comparison of SLAM algorithms that allows to find the most accurate one. The accent of research is made on 2D SLAM algorithms and the focus of analysis is 2D map that is built after algorithm performance. Three metrics for evaluation of maps are presented in this paper.

关键词： Simultaneous localization and mapping Measurement Trajectory Two dimensional displays algorithm design and analysis Mobile communication

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A Visualization Tool for Observing Metaheuristic algorithm: Epanel

A Visualization Tool for Observing Metaheuristic Algorithm: ...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Chou, Yao-Hsin Kuo, Shu-Yu Lai, Wei-Jie Lai, Wang-Bin Department of Electrical and Computer Engineering University of Denver Denver USA Department of Electrical and Computer Engineering Howard University Washington DC USA

ISBN: (纸本)9781538616451

Metaheuristic algorithms are important methods to solve many complicated optimization problems. However, there are no significant studies that present an application to analyze metaheuristic algorithms or a platform to help beginners to learn about. For this reason, we design a useful tool with a graphical user interface, EPanel, to dynamically display the process of metaheuristic algorithms. EPanel displays the value of a function in one or two dimensions by using different colors. It helps users understand the distribution of the solution space, such as unimodal, multimodal, and narrow valley. EPanel then shows the position of every particle above the screen of a function in each iteration and displays the complete optimization process of the algorithm by animation. Implemented with JAVA, EPanel is able to be executed in different operating systems. EPanel helps researchers to analyze each step of the algorithm and to observe how the algorithm achieves exploratory and exploitation. By using EPanel, research can further develop or improve algorithms efficiently. Beginners can learn about metaheuristic algorithms through EPanel. They can see popular algorithms, such as Particle Swarm Optimization and Artificial Bee Colony, work in each movement. EPanel is a useful application and helps not only researchers but also beginners.

关键词： Optimization algorithm design and analysis Heuristic algorithms Tools Image color analysis Animation Particle swarm optimization

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Dynamic Switch-Controller Association and Control Devolution for SDN Systems

Dynamic Switch-Controller Association and Control Devolution...

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IEEE International Conference on Communications (ICC) / Wireless Communications Symposium / 3rd Workshop on Optical Wireless Communications (OWC)

作者： Huang, Xi Bian, Simeng Shao, Ziyu Xu, Hong ShanghaiTech Univ Sch Informat Sci & Technol Shanghai Peoples R China City Univ Hong Kong NetX Lab Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781467389990

In software-defined networking (SDN), as data plane scale expands, scalability and reliability of the control plane have become major concerns. To mitigate such concerns, two kinds of solutions have been proposed separately. One is multicontroller architecture, i.e., a logically centralized control plane with physically distributed controllers. The other is control devolution, i.e., delegating control of some flows back to switches. Most of existing solutions adopt either static switch-controller association or static devolution, which may not adapt well to the traffic variation, leading to high communication costs between switches and controller, and high computation costs of switches. In this paper, we propose a novel scheme to jointly consider both solutions, i.e., we dynamically associate switches with controllers and dynamically devolve control of flows to switches. Our scheme is an efficient online algorithm that does not need the statistics of traffic flows. By adjusting some parameter V, we can make a trade-off between costs and queue backlogs. Theoretical analysis and extensive simulations show that our scheme yields much lower costs and latency compared to static schemes, and balanced loads among controllers.

关键词： Switches Process control Computational efficiency algorithm design and analysis Heuristic algorithms Reliability

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A graph theoretical approach for performance comparison of ICA for fMRI analysis 51

A graph theoretical approach for performance comparison of I...

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51st Annual Conference on Information Systems and Sciences (CISS)

作者： Long, Qunfang Bhinge, Suchita Levin-Schwartz, Yuri Calhoun, Vince D. Adali, Tulay Univ Maryland Baltimore Cty Dept Comp Sci & Elect Engn Baltimore MD 21250 USA Mind Res Network Albuquerque NM 87131 USA Univ New Mexico Dept Elect & Comp Engn Albuquerque NM 87131 USA

ISBN: (纸本)9781509047802

Due to its relatively few assumptions, independent component analysis (ICA) has become a widely-used tool for the analysis of functional magnetic resonance imaging (fMRI) data. In its application, Infomax, has been by far the most frequently used ICA algorithm, primarily because it is the first ICA algorithm applied to fMRI analysis. However, now there are a number of more flexible ICA algorithms, which can exploit multiple types of statistical properties of the signals with fewer assumptions. In this work, we investigate the performance of Infomax and two of the more recent ICA algorithms, entropy bound minimization (EBM) and entropy rate bound minimization (ERBM), on resting state fMRI data derived from a large number of patients with schizophrenia (SZs) and healthy controls (HCs). In order to overcome the difficulty of directly comparing the performances of different ICA algorithms on real fMRI data, we propose the use of graph theoretic (GT) metrics to assess the quality of an ICA decomposition by measuring an algorithm's ability to capture the inherent differences between SZs and HCs. Our results show that ERBM, the algorithm which incorporates the greatest number of statistical properties of the signals, provides the best performance for fMRI analysis.

关键词： algorithm design and analysis Entropy Integrated circuits Clustering algorithms Frequency measurement Minimization

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Exploring Heterogeneous algorithms for Accelerating Deep Convolutional Neural Networks on FPGAs 17

Exploring Heterogeneous Algorithms for Accelerating Deep Con...

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54th ACM/EDAC/IEEE design Automation Conference (DAC)

作者： Xiao, Qincheng Liang, Yun Lu, Liqiang Yan, Shengen Tai, Yu-Wing Peking Univ EECS Ctr Energy Efficient Comp & Applicat Beijing Peoples R China Chinese Univ Hong Kong Dept Informat Engn Hong Kong Hong Kong Peoples R China SenseTime Grp Ltd Shatin Hong Kong Peoples R China

ISBN: (纸本)9781450349277

Convolutional neural network (CNN) finds applications in a variety of computer vision applications ranging from object recognition and detection to scene understanding owing to its exceptional accuracy. There exist different algorithms for CNNs computation. In this paper, we explore conventional convolution algorithm with a faster algorithm using Winograd's minimal filtering theory for efficient FPGA implementation. Distinct from the conventional convolution algorithm, Winograd algorithm uses less computing resources but puts more pressure on the memory bandwidth. We first propose a fusion architecture that can fuse multiple layers naturally in CNNs, reusing the intermediate data. Based on this fusion architecture, we explore heterogeneous algorithms to maximize the throughput of a CNN. We design an optimal algorithm to determine the fusion and algorithm strategy for each layer. We also develop an automated toolchain to ease the mapping from Caffe model to FPGA bitstream using Vivado HLS. Experiments using widely used VGG and AlexNet demonstrate that our design achieves up to 1.99X performance speedup compared to the prior fusion-based FPGA accelerator foe CNNs.

关键词： algorithm design and analysis Field programmable gate arrays Computer architecture Bandwidth Kernel Pipelines Heuristic algorithms

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Minerva: Automated Hardware Optimization Tool

Minerva: Automated Hardware Optimization Tool

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International Conference on Reconfigurable Computing and FPGAs (ReConFig)

作者： Farahmand, Farnoud Ferozpuri, Ahmed Diehl, William Gaj, Kris George Mason Univ Dept Elect & Comp Engn Fairfax VA 22030 USA

ISBN: (纸本)9781538637975

A common way of determining the maximum clock frequency of a digital system is static timing analysis provided by CAD toolsets, such as Xilinx Vivado, Xilinx ISE, and Intel Quartus Prime. Finding the actual maximum clock frequency is difficult, especially in Xilinx Vivado, due to the multitude of tool options, and a complex dependence between the requested clock frequency and the actual clock frequency achieved by the tool. For example, a binary search to find maximum frequency is tedious, time-consuming, and often does not obtain the correct result. In this research, we introduce an automated hardware optimization tool called Minerva. Minerva determines the close-to-optimal settings of tools, using static timing analysis and a heuristic algorithm developed by the authors, and targets either optimal throughput or throughput-to-area (TPA) ratio. We apply Minerva to the hardware benchmarking of authenticated cipher candidates competing in the CAESAR cryptographic contest, where best TPA ratio (without any specific target for maximum clock frequency) is one metric by which winners are selected. We evaluate RTL designs of 29 Round 2 CAESAR candidates and the current standard, AES-GCM, in terms of throughput and TPA ratio. Compared to a binary search for maximum frequency, our results demonstrate up to 25% improvement in terms of throughput, and up to 38% improvement in terms of TPA ratio.

关键词： Clocks Tools Hardware Optimization Timing algorithm design and analysis Field programmable gate arrays

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How to Stop Consensus algorithms, locally? 56

How to Stop Consensus Algorithms, <i>locally</i>?

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56th Annual IEEE Conference on Decision and Control (CDC)

作者： Xie, Pei You, Keyou Wu, Cheng

ISBN: (纸本)9781509028733

This paper studies problems on locally stopping distributed consensus algorithms over networks where each node updates its state by interacting with its neighbors and decides by itself whether certain level of agreement has been achieved among nodes. Since an individual node is unable to access the states of those beyond its neighbors, this problem becomes challenging. In this work, we first define the stopping problem for generic distributed algorithms. Then, a distributed algorithm is explicitly provided for each node to stop consensus updating by exploring the relationship between the so-called local and global consensus. Finally, we show both in theory and simulation that its effectiveness depends both on the network size and the structure.

关键词： Distributed algorithms Protocols algorithm design and analysis Monitoring Eigenvalues and eigenfunctions Network topology Convergence

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