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12th RSI International Conference on Robotics and Mechatronics, ICRoM 2024

作者： Ghods, Amir Ahmad Doostmohammadian, Mohammadreza Semnan University Faculty of Mechanical Engineering Iran Semnan University Faculty of Mechanical Engineering Mechatronics Department Iran

ISBN: (纸本)9798331529734

Mobile target tracking is crucial in various applications such as surveillance and autonomous navigation. This study presents a decentralized tracking framework utilizing a Consensus-Based Estimation Filter (CBEF) integrated with the Nearly-Constant-Velocity (NCV) model to predict a moving target's state. The framework facilitates agents in a network to collaboratively estimate the target's position by sharing local observations and achieving consensus despite communication constraints and measurement noise. A saturation-based filtering technique is employed to enhance robustness by mitigating the impact of noisy sensor data. Simulation results demonstrate that the proposed method effectively reduces the Mean Squared Estimation Error (MSEE) over time, indicating improved estimation accuracy and reliability. The findings underscore the effectiveness of the CBEF in decentralized environments, highlighting its scalability and resilience in the presence of uncertainties. © 2024 IEEE.

关键词： Consensus-Based Es-timation Filter decentralized algorithms Mobile target tracking Nearly-Constant- Velocity model

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decentralized Coordinated Motion for Robot Teams Preserving Connectivity and Avoiding Collisions

Decentralized Coordinated Motion for Robot Teams Preserving ...

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作者： Anqi Li Carnegie Mellon University

学位级别：硕士

In this thesis, we consider the general problem of moving a large number of networked robots toward a goal position through a cluttered environment under con- straints on network connectivity and collision avoidance. In contrast to previous approaches that either plan complete paths for each individual robot in the high- dimensional joint configuration space or control the robot group as a whole with ex- plicit constraints on the group's boundary and inter-robot pairwise distances, we pro- pose a novel decentralized online behavior-based algorithm that relies on the topo- logical structure of the multi-robot communication and sensing graphs to solve this problem. We formally describe the communication graph as a simplicial complex that enables robots to iteratively identify the frontier nodes and coordinate forward motion through the sensing graph. This approach is proved to automatically deform robot teams for collision avoidance and always preserve connectivity. The effective- ness of our approach is demonstrated using numerical simulations. The algorithm is shown to scale linearly in the number of robots.

关键词： Multi-Robot Systems decentralized algorithms Algebraic Topology

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decentralized inertial best-response with voluntary and limited communication in random communication networks

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AUTOMATICA 2022年 145卷

作者： Aydin, Sarper Eksin, Ceyhun Texas A&M Univ Ind & Syst Engn Dept College Stn TX 77843 USA

Multiple autonomous agents interact over a random communication network to maximize their individual utility functions which depend on the actions of other agents. We consider decentralized best-response with inertia type algorithms in which agents form beliefs about the future actions of other players based on local information, and take actions that maximize their expected utilities computed with respect to these beliefs or continue to take their previous actions. We show convergence of these types of algorithms to a Nash equilibrium in weakly acyclic games. The result depends on the condition that the belief update and information exchange protocols successfully learn the actions of other players with positive probability in finite time given a static environment, i.e., when other agents' actions do not change. We design a decentralized fictitious play algorithm with voluntary and limited communication (DFP-VL) protocols that satisfy this condition. In the voluntary communication protocol, each agent decides whom to exchange information with by assessing the novelty of its information and the potential effect of its information on others' beliefs. The limited communication protocol entails agents sending only their most frequent action to agents that they decide to communicate with. Numerical experiments on a target assignment game demonstrate that the voluntary and limited communication protocol can more than halve the number of communication attempts while retaining the same convergence rate as DFP in which agents constantly attempt to communicate. (C) 2022 Elsevier Ltd. All rights reserved.

关键词： Multi-agent systems Game theory decentralized algorithms

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decentralized Connectivity Maintenance for Multi-Robot Systems Under Motion and Sensing Uncertainties

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NAVIGATION-JOURNAL OF THE INSTITUTE OF NAVIGATION 2023年第1期70卷

作者： Shetty, Akshay Hussain, Timmy Gao, Grace Stanford Univ Dept Aeronaut & Astronaut Stanford CA USA Stanford Univ Dept Aeronaut & Astronaut Stanford CA 94305 USA

Communication connectivity is desirable for the safe and efficient operation of multi-robot systems. While decentralized algorithms for connectivity mainte-nance have been explored in recent literature, the majority of these works do not account for robot motion and sensing uncertainties. These uncertainties are inherent in practical robots and result in robots deviating from their desired positions which could potentially result in a loss of connectivity. In this paper, we present a decentralized connectivity maintenance algorithm accounting for robot motion and sensing uncertainties (DCMU). We, first, propose a novel weighted graph definition for the multi-robot system that accounts for the afore-mentioned uncertainties along with realistic connectivity constraints such as line-of-sight connectivity and collision avoidance. We, then, design a decen-tralized gradient-based controller for connectivity maintenance with which we derive the gradients of the weighted graph edge weights required for computing the control. Finally, we perform multiple simulations to validate the connectiv-ity maintenance performance of our DCMU algorithm under robot motion and sensing uncertainties, showing an improvement compared to previous work.

关键词： connectivity maintenance motion and sensing uncertainties decentralized algorithms gradient-based control multi-robot systems

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Price-Based Protocols for Fair Resource Allocation: Convergence Time Analysis and Extension to Leontief Utilities

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ACM TRANSACTIONS ON algorithms 2014年第2期10卷 5-5页

作者： Goel, Ashish Nazerzadeh, Hamid Stanford Univ Dept Management Sci & Engn Stanford CA 94305 USA Univ So Calif Operat Management Dept Marshall Sch Business Los Angeles CA USA

We analyze several distributed, continuous time protocols for a fair allocation of bandwidths to flows in a network (or resources to agents). Our protocols converge to an allocation that is a logarithmic approximation, simultaneously, to all canonical social welfare functions (i.e., functions that are symmetric, concave, and nondecreasing). These protocols can be started in an arbitrary state. Although a similar protocol was known before, it only applied to the simple bandwidth allocation problem, and its stability and convergence time were not understood. In contrast, our protocols also apply to the more general case of Leontief utilities, where each user may place a different requirement on each resource. Furthermore, we prove that our protocols converge in polynomial time. The best convergence time we prove is O(n log (nc)MAX(alpha)MAX / (MINMIN)-M-c-M-alpha), where n is the number of agents in the network, c(MAX) and c(MIN) are the maximum and minimum capacity of the links, and alpha(max), alpha(min) are respectively the largest and smallest Leontief coefficients. This time is achieved by a simple Multiplicative Increase, Multiplicative Decrease (MIMD) protocol that had not been studied before in this setting. We also identify combinatorial properties of these protocols that may be useful in proving stronger convergence bounds. The final allocations by our protocols are supported by usage-sensitive dual prices that are fair in the sense that they shield light users of a resource from the impact of heavy users. Thus, our protocols can also be thought of as efficient distributed schemes for computing fair prices.

关键词： Network protocols fairness shadow prices decentralized algorithms Leontief utilities majorization

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decentralized and Optimal Control of Shared Resource Pools

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ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS 2012年第1期7卷 14-14页

作者： Loureiro, Emerson Nixon, Paddy Dobson, Simon Univ Coll Dublin Sch Comp Sci & Informat Syst Res Grp Dublin 6 Ireland

Resource pools are collections of computational resources (e.g., servers) which can be used by different applications in a shared way. A crucial aspect in these pools is to allocate resources so as to ensure their proper usage, taking into account workload and specific requirements of each application. An interesting approach, in this context, is to allocate the resources in the best possible way, aiming at optimal resource usage. Workload, however, varies over time, and in turn, resource demands will vary too. To ensure that optimal resource usage is always in place, resource shares should be defined dynamically and over time. It has been claimed that utility functions are the main tool for enabling such self-optimizing behavior. Whereas many solutions with this characteristic have been proposed to date, none of them presents true decentralization within the context of shared pools. In this article, we then propose a decentralized model for optimal resource usage in shared resource pools, providing practical and theoretical evidence of its feasibility.

关键词： algorithms decentralized algorithms decentralized optimization resource management utility maximization resource pools

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Optimal Resource Allocation in Sparse Networks

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IFAC Proceedings Volumes 1981年第2期14卷 1451-1456页

作者： P.L. McEntire R.E. Larson Systems Control Inc. 1801 Page Mill Road Palo Alto CA 94304 USA

A method for optimally allocating resources in a distributed network of sources and sinks is presented. The method is a version of dynamic programming which exploits the sparsity of interconnections in the network. One unusual property of the method is its ability to be implemented on a distributed computer network, with the bulk of the computations distributed among the nodes of the network. Two examples are presented. The first determines the optimal generation levels in an electric power network; the second finds the best allocation of processors to computing tasks in a distributed computer network.

关键词： Resource allocation sparse networks distributed computing dynamic programming decentralized algorithms optimal power flow

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Fault Tolerant Area Coverage Using Underwater Vehicles

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IFAC Proceedings Volumes 2012年第5期45卷 94-99页

作者： José Braga Pedro Calado P.B. Sujit J.B. Sousa Department of Electrical and Computer Engineering University of Porto Portugal - 4200-465

Multiple autonomous underwater vehicles (AUVs) can be deployed to map large regions. For mapping, the desired motion plan must be lawn mover pattern to scan the bottom. In addition to motion plan constraints, AUVs are subject to limited sensing and communication ranges and some of the AUVs can fail while performing the assigned mission leg. Developing an efficient fault tolerant area coverage controller with these constraints is a difficult task. In this paper, we develop a consensus based fault tolerant area coverage controller that takes the uncertainty in environments, communication range constraints and AUV failures while covering the area with limited repeated coverage. Current approach is able to deal with agent faults located in the middle of a series of AUVs. Simulations are presented to validate the approach.

关键词： decentralized algorithms Fault tolerance Cooperative coverage Autonomous vehicles Multi vehicle control Marine systems

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decentralized stochastic gradient Langevin dynamics and Hamiltonian Monte Carlo

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2021年第1期22卷 10804-10872页

作者： Mert Gürbüzbalaban Xuefeng Gao Yuanhan Hu Lingjiong Zhu Department of Management Science and Information Systems Rutgers Business School Piscataway NJ Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin N.T. Hong Kong China Department of Mathematics Florida State University Tallahassee FL

Stochastic gradient Langevin dynamics (SGLD) and stochastic gradient Hamiltonian Monte Carlo (SGHMC) are two popular Markov Chain Monte Carlo (MCMC) algorithms for Bayesian inference that can scale to large datasets, allowing to sample from the posterior distribution of the parameters of a statistical model given the input data and the prior distribution over the model parameters. However, these algorithms do not apply to the decentralized learning setting, when a network of agents are working collaboratively to learn the parameters of a statistical model without sharing their individual data due to privacy reasons or communication constraints. We study two algorithms: decentralized SGLD (DE-SGLD) and decentralized SGHMC (DE-SGHMC) which are adaptations of SGLD and SGHMC methods that allow scaleable Bayesian inference in the decentralized setting for large datasets. We show that when the posterior distribution is strongly log-concave and smooth, the iterates of these algorithms converge linearly to a neighborhood of the target distribution in the 2-Wasserstein distance if their parameters are selected appropriately. We illustrate the efficiency of our algorithms on decentralized Bayesian linear regression and Bayesian logistic regression problems.

关键词： Langevin dynamics Hamiltonian Monte Carlo decentralized algorithms decentralized Bayesian inference stochastic gradient momentum acceleration heavy-ball method convergence rate Wasserstein distance

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decentralized EXTREMA-FINDING IN CIRCULAR CONFIGURATIONS OF PROCESSORS

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COMMUNICATIONS OF THE ACM 1980年第11期23卷 627-628页

作者： HIRSCHBERG, DS SINCLAIR, JB Rice Univ. Houston TX Rice Univ. Houston TX

Examines a decentralized extrema-finding algorithm in a circular configurations of processors for data transmission. Use of algorithm in determining the capability of processors to pass a message in a global sense; Capability of the processor to initiate messages in a sendboth directive; Data transmissions in the complex algorithm.

关键词： decentralized algorithms distributed system operating systems

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