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A distributed approach for road clearance with multi-robot in urban search and rescue environment

INTERNATIONAL JOURNAL OF INTELLIGENT ROBOTICS AND APPLICATIONS 2019年第4期3卷 392-406页

作者： Nath, Amar Arun, A. R. Niyogi, Rajdeep Indian Inst Technol Roorkee Roorkee 247667 Uttar Pradesh India

In urban search and rescue domains, robots explore the affected terrain to search and assist disaster victims. RoboCup Rescue simulation provides a platform for disaster management where heterogeneous field agents (fire-brigade agent, ambulance agent, and police force agent) collaborate to manage a mimicked calamity situation. The role of police force agents is crucial, as they clear the blocked roads to allow other agents to perform their tasks. In this paper we suggest a distributed multi-robot coordination approach for clearing a road blocked with heavy obstacles. The proposed framework is implemented and simulated in ARGoS, a multi-robot simulator. The experimental results show the validity and satisfactory performance of the proposed approach.

关键词： Urban search and rescue Multi-robot coordination Task allocation distributed algorithm

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A dynamic pricing scheme for electric vehicle in photovoltaic charging station based on Stackelberg game considering user satisfaction

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 154卷 107117-107117页

作者： Dai, Yeming Qi, Yao Li, Lu Wang, Baohui Gao, Hongwei Qingdao Univ Sch Business Qingdao 200071 Peoples R China Qingdao Univ Sch Math & Stat Qingdao 200071 Peoples R China Shandong Univ Sch Econ Jinan 250199 Peoples R China

Electric vehicle (EV) has increasingly become an important part of the load of smart power grid in recent years. Since uncoordinated EV would stress the distributed grid system, the establishment of Photovoltaic (PV) charging station is of great significance to optimizing domestic power demand and developing a low-carbon society. In this paper, a dynamic pricing scheme based on Stackelberg game for EV charging station with PV system is proposed. Considering the uncertainty of electricity changes before and after charging, we divide one day into two kinds of time intervals: charging time interval and pricing time interval, and the demand response (DR) based on preference of EV user is also implemented. Moreover, the constraint reflecting the fluctuation (uncertainty) of power consumption caused by the charging continuity of EV is also introduced to the model. By analyzing the probability property of constraints, the game model with uncertainty is equivalently transformed into a convex game at the end. Additionally, the existence and uniqueness of Stackelberg Equilibrium (SE) is proved, so the optimal strategies of all participants are guaranteed. Finally, a distributed algorithm is designed to obtain the SE. The simulation results show that the pricing scheme proposed in this paper can better reduce the selling price of charging station and increase the profit of charging station.

关键词： Photovoltaic charging station Electric vehicles Dynamic pricing Stackelberg game User satisfaction distributed algorithm

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distributed Continuous-time algorithm to Solve a Linear Matrix Equation

Distributed Continuous-time Algorithm to Solve a Linear Matr...

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IEEE International Conference on Real-time Computing and Robotics (IEEE RCAR)

作者： Deng, Wen Zeng, Xianlin Hong, Yiguang Chinese Acad Sci Acad Math & Syst Sci LSC Beijing Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing Peoples R China Beijing Inst Technol Sch Automat Key Lab Intelligent Control & Decis Complex Syst Beijing Peoples R China Chinese Acad Sci Acad Math & Syst Sci Key Lab Syst & Control Beijing Peoples R China

ISBN: (纸本)9781538668696

We study the distributed solving process of one class of linear matrix equations such as Sigma(r)(i=1) A(i)XB(i) = Sigma C-r(i=1)i, using a continuous-time optimization method over multi-agent networks In the problem formulation, each agent i is aware of A(i), B-i,C-i and communicates with its neighbors. Next, a continuous-time distributed algorithm presented is to solve its least squares solution from a distributed constrained optimization viewpoint. With help of the Lyapunov stability and semi-stability analysis, we prove the convergence of the algorithm and provide two numerical examples.

关键词： Multi-agent networks distributed algorithm matrix equation optimal solution semi-stability

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A Unified Sparsification Approach for Matching Problems in Graphs of Bounded Neighborhood Independence 20

A Unified Sparsification Approach for Matching Problems in G...

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32nd ACM Symposium on Parallelism in algorithms and Architectures (SPAA)

作者： Milenkovic, Lazar Solomon, Shay Tel Aviv Univ Sch Elect Engn Tel Aviv Israel

ISBN: (纸本)9781450369350

The neighborhood independence number of a graph G, denoted by beta = beta(G), is the size of the largest independent set in the neighborhood of any vertex. Graphs with bounded neighborhood independence, already for constant beta, constitute a wide family of possibly dense graphs, including line graphs, unit-disk graphs, claw-free graphs and graphs of bounded growth, which has been well-studied in the area of distributed computing. In ICALP'19, Assadi and Solomon [8] showed that, for any n-vertex graph G, a maximal matching can be computed in O(n log n . beta) time in the classic sequential setting. This result shows that, surprisingly, for almost the entire regime of parameter beta, a maximal matching can be computed much faster than reading the entire input. The algorithm of [8], however, is inherently sequential and centralized. Moreover, a maximal matching provides a 2-approximate (maximum) matching, and the question of whether a better-than-2-approximate matching can be computed in sublinear time remained open. In this work we propose a unified and surprisingly simple approach for producing (1 + epsilon)-approximate matchings, for arbitrarily small epsilon > 0. Specifically, set Delta = O(beta/epsilon log 1/epsilon) and let G(Delta) be a random subgraph of G that includes, for each vertex v is an element of G, Delta random edges incident on it. We show that, with high probability, G(Delta) is a (1 + epsilon-matching sparsifier for G, i.e., the maximum matching size of G(Delta) is within a factor of 1 + epsilon from that of G. One can then work on the sparsifier G(Delta) rather than on the original graph G. Since G(Delta) can be implemented efficiently in various settings, this approach is of broad applicability;some concrete implications are: A (1 + epsilon)-approximate matching can be computed in the classic sequential setting in O(***/epsilon(2) . log 1/epsilon) time, shaving a log n factor from the runtime of [8] (for any constant c), and more importantly

关键词： distributed algorithm graph matching maximum matching neighborhood independence sublinear time sparsification

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Joint User Scheduling and Beam Selection in mmWave Networks Based on Multi-Agent Reinforcement Learning 11

Joint User Scheduling and Beam Selection in mmWave Networks ...

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IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM)

作者： Xu, Chunmei Liu, Shengheng Zhang, Cheng Huang, Yongming Yang, Luxi Southeast Univ Sch Informat Sci & Engn Nanjing 210096 Peoples R China Purple Mt Labs Nanjing 210096 Peoples R China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119465

In this paper, we consider a multi-cell downlink mmWave communication network and investigate an efficient transmission scheme for all base stations. Since the beams are highly directed with respected to the user equipments, user scheduling and beam selection strategy should be jointly considered. The objective is to develop the joint user scheduling and beam selection strategy that minimizes the long-term average delay cost while satisfying the instantaneous quality of service constraint of each user. To achieve the long-term performance, a distributed algorithm is proposed to develop the joint strategy based on multi-agent reinforcement learning. Simulation results validate the effectiveness of the proposed intelligent distributed method.

关键词： Millimeter wave communication user scheduling beam selection distributed algorithm multi-agent reinforcement learning

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Collaborative Evacuation of Mobile Robots 20

Collaborative Evacuation of Mobile Robots

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21st International Conference on distributed Computing and Networking (ICDCN)

作者： Pattanayak, Debasish Ramesh, H. Mandal, Partha Sarathi Indian Inst Technol Guwahati Gauhati India IIT Guwahati Gauhati India

ISBN: (纸本)9781450377515

distributed evacuation of mobile robots has recently raised the interest of researchers. Czyzowicz et al. [1] introduced the evacuation problem minimizing the time required for the last searcher to reach the target. They showed the optimal evacuation time for two robots in the wireless model while achieved an upper and lower bound for two robots in the face-to-face model. This has been further improved in subsequent papers. The objective is to plan the path of robots such that the worst-case evacuation time can be minimized. In a variation with faulty robots not able to detect the exit, Czyzowicz et al. [2] focused on minimizing the evacuation time for the latest non-faulty robot. They presented a lower and upper bound for three robots where at most one is susceptible to crash fault with wireless communication. Please refer [3] for detailed related *** and Problems. The two robots, initially located at the center of a unit disk, have to evacuate the disk through the two exits situated on the perimeter of the disk at unknown locations. The distance d between the two exits along the perimeter is given. The robots communicate either in the wireless model (sending messages over a long distance) or the face-to-face model (exchange of information is possible by meeting). The objective is to minimize the worst-case evacuation time in both the wireless and face-to-face communication model for two robots with two exits (labeled or unlabeled). The second problem considers a robot can become faulty at any point of time during evacuation. Instead of abandoning the crashed robot, the non-faulty robot chauffeurs it to the exit. It takes α ≥ 1 amount of time to chauffeur for unit distance. The objective is to minimize the worst-case evacuation time even in the presence of one faulty robot with a single exit on the ***. Given two exits located on the perimeter of a unit disk, there are two variations considered. An exit can be labeled or unlabeled. A robot at a lab

关键词： Mobile Robots Evacuation distributed algorithm

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Reward-Punishment based User Utility Maximization Model for Optimal Real-time Pricing in Electricity Energy Supply

Reward-Punishment based User Utility Maximization Model for ...

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IEEE-Power-and-Energy-Society Innovative Smart Grid Technologies Conference (ISGT)

作者： Wang, Lele Chen, Jia-Jia Zeng, Shunqi Liu, Lei Peng, Ke Shandong Univ Technol Sch Elect & Elect Engn Zibo 255000 Peoples R China Guangzhou Power Supply Bur Co Ltd Guangzhou 510620 Guangdong Peoples R China

ISBN: (数字)9781728131030

ISBN: (纸本)9781728131030

Due to uncertainty factors such as renewable energy, imbalance between supply and demand has a great impact on the stable operation of the smart grid. The demand response (DR) program can effectively solve the imbalance issue by guiding users to adopt reasonable electricity consumption manner. In addition, users should be able to benefit from participating in DR by changing the habit of using energy. In the present study, a dynamic reward-punishment based user utility maximization model is proposed for optimal real-time pricing (RTP) in electricity energy supply to reach the supply-demand balance and provide the optimal reward and punishment for users. Based on the dynamic reward and punishment mechanism, the proposed model can obtain the optimal electricity consumption by maximizing user utility and encourage users to adopt a reasonable electricity consumption manner. From the perspective of algorithm implementation, a distributed algorithm is proposed to achieve the purpose of the supply-demand balance with the optimal electricity price and optimal electricity consumption. The simulation results show that the proposed utility model and distributed algorithm are reasonable and effective in dealing with the imbalance problem between supply and demand.

关键词： Demand response Real-time pricing Reward-punishment mechanism User utility maximization distributed algorithm

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Information Value on Private State Inference in Network Systems 21st

Information Value on Private State Inference in Network Syst...

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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Jiang, Hao Ding, Xuda He, Jianping Peng, Yunfeng Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

In network systems, neighboring nodes usually need to exchange and update their state information iteratively to achieve a global computation and control goal. Considering the nodes' states may include some sensitive/private information, e.g., location and income, different random mechanizes have been proposed to preserve the privacy of the states. However, no matter what type of random mechanisms is used, the eavesdropping attacker can infer/estimate a node's state based on the information it holds, and the estimation depends on the available information. The relationship between the estimation and the information is a critical and open issue. Therefore, in this paper, we investigate how to obtain the optimal estimation of a node's state with available information and how to quantify the value of the information in the state inference. First, we exploit a utility function to quantify the utility of the estimation accuracy, and then the optimal estimation and information value are defined to depict the estimation and quantify the information, respectively. Next, the optimal estimation under different settings of the noise and utility function is provided. Lastly, we obtain some essential properties of information value and analyze the value of state outputs in distributed algorithms. Copyright (C) 2020 The Authors.

关键词： distributed algorithm Noise adding process Optimal estimation Data privacy Average consensus

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distributedly Solving Boolean Equations over Networks 59

Distributedly Solving Boolean Equations over Networks

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59th IEEE Conference on Decision and Control (CDC)

作者： Qi, Hongsheng Li, Bo Jing, Rui-Juan Proutiere, Alexandre Shi, Guodong Chinese Acad Sci Acad Math & Syst Sci Inst Syst Sci Key Lab Syst & Control Beijing Peoples R China Univ Chinese Acad Sci Sch Math Sci Beijing 100049 Peoples R China Chinese Acad Sci Acad Math & Syst Sci Key Lab Math Mechanizat Beijing Peoples R China Jiangsu Univ Fac Sci Zhenjiang 212013 Jiangsu Peoples R China KTH Royal Inst Technol Dept Automat Control S-10044 Stockholm Sweden Univ Sydney Australian Ctr Field Robot Sch Aerosp Mech & Mechatron Engn Sydney NSW Australia

ISBN: (纸本)9781728174471

In this paper, we propose distributed algorithms that solve a system of Boolean equations over a network, where each node in the network possesses only one Boolean equation from the system. The Boolean equation assigned at any particular node is a private equation known to this node only, and the nodes aim to compute the exact set of solutions to the system without exchanging their local equations. We show that each private Boolean equation can be locally lifted to a linear algebraic equation under a basis of Boolean vectors, leading to a network linear equation that is distributedly solvable. A number of exact or approximate solutions to the induced linear equation are then computed at each node from different initial values. The solutions to the original Boolean equations are eventually computed locally via a Boolean vector search algorithm. We prove that given solvable Boolean equations, when the initial values of the nodes for the distributed linear equation solving step are i.i.d selected according to a uniform distribution in a high-dimensional cube, our algorithms return the exact solution set of the Boolean equations at each node with high probability.

关键词： distributed algorithm Boolean equation

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A Multi-layer and Vanet-based Approach to Improve Accident Management in Smart Cities 16

A Multi-layer and Vanet-based Approach to Improve Accident M...

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16th Annual International Conference on distributed Computing in Sensor Systems (DCOSS)

作者： Brandao, Yan, V De Souza, Lucas M. Gomides, Thiago S. De Grande, Robson E. Souza, Fernanda S. H. Guidoni, Daniel L. Univ Fed Sao Joao del Rei Dept Comp Sci Sao Joao Del Rei MG Brazil Brock Univ Dept Comp Sci St Catharines ON Canada

ISBN: (纸本)9781728143514

The growth in the number of traffic accidents has become a cause for concern in urban centers. As a result of the increase in population in large cities and the number of vehicles, the consequences of accidents and congestion can be even more significant, considering the impacts on the economy, environment and people's quality of life. Therefore, aiming to minimize these impacts, we present ALIVE, a distributed and Vanet-based solution that reduces congestion caused by different sources and, especially, from accident sources, contributing to efficient urban mobility in smart cities. The solution performs the detection of accidents and the dissemination of warning messages in multiple hops. Besides, the system can share the road traffic information with the nearby streets to improve traffic efficiency. We evaluated the proposed solution with PANDORA and NRR Traffic Management solutions. Simulation results indicate that the proposed solution reduces the average travel time, time lost, and the number of transmitted messages.

关键词： Smart city multi-layer distributed algorithm traffic and congestion management

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