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Conference on Signal Processing, Sensor Fusion, and Target Recognition XIV

作者： Sathyan, T Sinha, A Kirubarajan, T McMaster Univ Elect & Comp Engn Dept Hamilton ON L8S 4K1 Canada

ISBN: (纸本)0819457949

Previous researches related to geolocation based on the time difference of arrival (TDOA) technique focused mainly on solving the nonlinear equations that relate the TDOA measurements to the unknown source location. They, however, considered a rather simplistic scenario: a single emitter with no possibility of either missed detections, or false measurements. In real world scenarios, one must resolve the important issue of measurement-origin uncertainty, before applying these techniques. This paper proposes an algorithm for the geolocation and tracking of multiple emitters in practical scenarios. The focus is on solving the all important data association problem, i.e., deciding from which target, if any, a measurement originated. A previous solution for data association based on the assignment formulation for passive measurement tracking systems relied on solving two assignment problems: an S-dimensional (or, SD, where S >= 3) assignment for association across sensors, and a 2D assignment for measurement-to-track association. Here, an (S + 1)D assignment algorithm, which performs the data association in one step, is introduced. As can be seen later, the (S + 1)D assignment formulation reduces the computational cost significantly. Incorporation of correlated measurements (which is the case with TDOA measurements) into the SD framework that typically assumes uncorrelated measurements, is also discussed. The nonlinear TDOA equations are posed as an optimization problem, and solved using SolvOpt - a nonlinear optimization solver. The interacting multiple model (IMM) estimator is used in conjunction with the unscented Kalman filter (UKF) to track the geolocated emitters.

关键词： geolocation multitarget/multisensor tracking TDOA data association assignment technique IMM estimator auction algorithm UKF

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Task Allocation Performance Comparison for Low Power Devices

Task Allocation Performance Comparison for Low Power Devices

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IEEE National Aerospace and Electronics Conference (NAECON)

作者： Rahman, Nayim Atahary, Tanvir Yakopcic, Chris Taha, Tarek M. Douglass, Scott Univ Dayton Elect & Comp Engn Dayton OH 45469 USA Air Force Res Lab Human Effectiveness Directorate Wright Patterson AFB OH USA

ISBN: (纸本)9781538665572

Cognitive agents are typically utilized in autonomous systems for automated decision making. These systems interact in real time with their environment and are generally heavily power constrained. Thus, there is a strong need for a real time agent running on a low power computing platform. An autonomous agent reasons like humans and enables enhanced agent-based decision-making. The agent examined is the Cognitively Enhanced Complex Event Processing (CECEP) architecture. Task allocation is one of most time consuming and power-hungry processes within the CECEP architecture. Task allocation is a combinatorial optimization problem in the field of operations research. In the CECEP architecture, the cognitive agent performs this task allocation. This paper examines the performance of two task allocation algorithms (the greedy algorithm and the auction algorithm) that have the potential to significantly reduce the power and energy required to perform this task. Thus, it may be possible to execute complex task allocation problems on custom, portable, low power devices.

关键词： cognitive agent autonomous decision making greedy algorithm auction algorithm low power hardware

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SOMETIMES THEY COME BACK: TESTING TWO SIMPLE HYPOTHESES (IN THE REALM OF UNLABELED DATA)

SOMETIMES THEY COME BACK: TESTING TWO SIMPLE HYPOTHESES (IN ...

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IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

作者： Marano, Stefano Willett, Peter Univ Salerno DIEM Fisciano SA Italy Univ Connecticut ECE Dept Storrs CT USA

ISBN: (纸本)9781538646588

Consider a binary hypothesis where data are independent and identically distributed under the null hypothesis, and known only to be independent under the alternative. The statistician observes an n-vector X-n (n >> 1) and makes a decision using the optimal likelihood ratio test. This seems a widely-known detection problem, but: What if only the set of samples of X-n are made available to the statistician, while the positions of the individual samples inside the vector are not? Does there exist an optimal test in that case? What is the fundamental performance limit? Are there nicely-performing practical detectors with affordable computational complexity? Answers to these questions are in large part unknown, despite the fact that the problem - which is becoming known under the name of unlabeled detection - is very relevant in modern sensor network applications where the sample positions can be lost due to their means of delivery from the remote units, or because of network attacks.

关键词： Unlabeled detection fundamental limits of detection auction algorithm

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A comparison of two algorithms for the assignment problem

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Computational Optimization and Applications 1995年第1期4卷 23-45页

作者： Zaki, Hossam A. SABRE Decision Technologies DFW Airport 75261-9616 TX Box 619616-MD4479 United States

State-of-the-art computational results have shown that the shortest augmenting path (SAP) methods are more efficient than other primal-dual and primal-simplex based methods for solving the linear assignment problem on uniprocessor computers. There is, however, some controversy concerning their merits when compared with Bertsekas' auction algorithm on multiprocessor computers. In this study we investigate the performance of these competing methods on the Alliant FX/8. For each method, theoretical motivation, sources of parallelism and computational results are presented. © 1995 Kluwer Academic Publishers.

关键词： auction algorithm parallel computing shortest augmenting path method

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Multi-agent Weapon Target Assignment and Cooperative Path Planning Based on QS-RRT algorithm 41

Multi-agent Weapon Target Assignment and Cooperative Path Pl...

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第41届中国控制会议

作者： Qingze Li Yongzhao Hua Haoran Zhai Qingdong Li Xiwang Dong School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control LaboratoryBeihang University Institute of Artificial Intelligence Beihang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,based on the typical combat scenario where multiple UAVs strike multiple targets,the model of weapon firepower allocation is firstly modeled to obtain the corresponding objective function,and then the improved distributed auction algorithm is used to solve the objective function to obtain the multi-target allocation *** layer first analyze the traditional RRT algorithm,and gets the quick and smooth convergence RRT(QS-RRT) on the basis of improved algorithm,the algorithm on the basis of adding the synergy of constraints,and makes the collaborative planning path compared with non-cooperative path planning,the planning path length in the keep basically remain unchanged,on the basis of our UAV for the same target can arriving together,The difference of arrival time is greatly reduced,and the subsequent coordinated strike mission can be completed more efficiently in the combat scenario.

关键词： Weapon target assignment auction algorithm Cooperative path planning QS-RRT algorithm

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Load Balance Optimization Based Multi-robot Cooperative Task Planning for Large-Scale Aerospace Structures 14th

Load Balance Optimization Based Multi-robot Cooperative Task...

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14th International Conference on Intelligent Robotics and Applications (ICIRA)

作者： Lin, Jiamei Tian, Wei Li, Pengcheng Lu, Shaorui Nanjing Univ Aeronaut & Astronaut Nanjing Peoples R China

ISBN: (纸本)9783030890988;9783030890971

Regarding the manufacturing and assembling requirements of large-scale structures in the aerospace industry, the existing large-scale machine tool integral manufacturing and offline split manufacturing methods have multiple limitations in cost, efficiency and quality. Taking advantages of flexibility, multi-robot system can be used for in-situ machining of large cabin, which has received extensive attention in the field of aerospace manufacturing. However, the research on multi-robot cooperative task planning is still insufficient, and there are problems such as uneven task allocation and difficult to eliminate interference between robots. This paper proposes a multi-robot cooperative task planning method to solve the problem of unbalanced load of multi-robot systems in the processing of large structures. The proposed algorithm utilizes the K-Means clustering principle to determine the base position of robots according to the density of task. The auction algorithm combined with the load distribution is studied to coordinate the assignment of tasks. The collision avoidance algorithm based on the unilateral coordination strategy is proposed to optimize the processing path of robots. The effectiveness of the algorithm in terms of time efficiency under different working conditions is demonstrated by the simulation of the large wing structure assembly. The results proved that the proposed algorithm effectively reduces the completion time and achieves the load balance of the multi-robot system. The proposed algorithm plans a conflict-free path and improves the efficiency of the multi-robot system.

关键词： Multi-robot system Base position planning auction algorithm Path planning Collision avoidance

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Maximizing Lifetime of Wireless Sensor Networks using Genetic Approach

Maximizing Lifetime of Wireless Sensor Networks using Geneti...

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4th IEEE International Advance Computing Conference (IACC)

作者： Wagh, Sanjeev Prasad, Ramjee Aalborg Univ Ctr TeleInfrastruktur CTIF Aalborg Denmark

ISBN: (纸本)9781479925711

The wireless sensor networks are designed to install the smart network applications or network for emergency solutions, where human interaction is not possible. The nodes in wireless sensor networks have to self organize as per the users requirements through monitoring environments. As the sensor nodes are deployed in an inaccessible location for particular mission, it is difficult to exchange or recharge the nodes battery. Hence the important issues to design the sensor network for maximum time duration of network and also for low power operation of the nodes. The proposal is to select the cluster head intelligently using auction data of node i.e. its local battery power, topology strength and external battery support. The network lifetime is the centre focus of the research paper which explores intelligently selection of cluster head using auction based approach. The multi-objective parameters are considered to solve the problem using genetic algorithm of evolutionary approach.

关键词： WSNs clustering lifetime genetic algorithm auction algorithm residual energy

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Research on Task Assignment Optimization algorithm Based on Multi-Agent

Research on Task Assignment Optimization Algorithm Based on ...

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Chinese Automation Congress (CAC)

作者： Zhang, Jie Wang, Gang Yao, Xiaoqiang Song, Yafei Zhao, Fangzheng Air Force Engn Univ Grad Sch Xian Shaanxi Peoples R China Air Force Engn Univ Air Def & Antimissile Acad Xian Shaanxi Peoples R China

ISBN: (纸本)9781728113128

This paper studies the task assignment problem in multi-agent field. The maximum number of tasks for a single agent and the number of agents required for a single task are taken as objective functions. Considering the characteristics of the air defense unmanned combat agent, the Multi-agent task allocation model based on the improved auction algorithm is established. The first step is to establish a mathematical model for the task assignment strategy and confirms the objective function. Then, the resource utilization efficiency is improved by optimizing the auction algorithm. Finally, the simulation experiments prove the effectiveness and convergence of the algorithm.

关键词： multi-agent task assignment auction algorithm resource utilization convergence

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Vehicle scheduling for suburban public transport

Vehicle scheduling for suburban public transport

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39th Latin American Computing Conference (CLEI)

作者： Alaggia, Sebastian Mauttone, Antonio Urquhart, Maria Univ Republica Fac Ingn Inst Computac Montevideo Uruguay

ISBN: (纸本)9781479913404;9781479929573

This paper studies the Vehicle Scheduling Problem (VSP) in the context of suburban passenger transportation. The problem consists in finding a set of sequences of trips which have to be assigned to the available fleet of buses. The complexity of this problem depends on the number of depots where the fleet is housed. The paper focuses on the resolution of Multiple Depot VSP (MDVSP) which has NP-Hard Complexity. A column generation heuristic is proposed to solve the problem, and two heuristic algorithms are used to provide a set of initial columns, one of them is based on the auction algorithm for Single Depot VSP (SDVSP). The algorithms where tested with a small instance and real world one, obtaining solutions which are either optimal or have lower cost and use less buses than the best known solution for a related and more complex problem.

关键词： Vehicle Scheduling MDVSP SDVSP Column Generation auction algorithm

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Multi-robot system task allocation mechanism for smart factory 8

Multi-robot system task allocation mechanism for smart facto...

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IEEE 8th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

作者： Huang, Yin Zhang, Yi Xiao, Hong Chongqing Univ Posts & Telecommun Res Ctr Intelligent Syst & Robot Chongqing Peoples R China

ISBN: (纸本)9781538681787

the smart factory has been developed many years, but the current situation of multi-robot task allocation mechanism only applicable to homogeneous robot systems, the problem of heterogeneous multi-robot cooperative task allocation is studied in this paper. A distributed auction algorithm is designed to classify different capabilities of robots with adopting atomic ability. The robot capability model and the task capability model are established, based on the distance between the robot and the target task and the matching degree between the robot capability and the task, a task allocation problem model is established to solve the problem of heterogeneous multi-robot collaborative task allocation. The simulation results show the correctness of the model and the effectiveness of the algorithm.

关键词： task allocation multi-robot system heterogeneous robots auction algorithm smart factory

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