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Effective coverage control for mobile sensor networks with guaranteed collision avoidance

IEEE TRANSACTIONS ON control SYSTEMS TECHNOLOGY 2007年第4期15卷 642-657页

作者： Hussein, Islam I. Stipanovic, Dusan M. Worcester Polytech Inst Dept Mech Engn Worcester MA 01609 USA Univ Illinois Dept Ind & Enterprise Syst Engn Urbana IL 61801 USA Univ Illinois Coordinated Sci Lab Urbana IL 61801 USA

This paper studies the problem of dynamically covering a given region in the plane using a set of mobile sensor agents. A novel problem formulation is proposed that addresses a number of important multiagent missions. The coverage goal, which is to cover a given search domain using multiple mobile sensors such that each point is surveyed until a certain preset level is achieved, is formulated in a mathematically precise problem statement. A control law is developed that guarantees to meet the coverage goal. This control law is modified to guarantee that a partially connected fleet also attains the coverage. goal. Finally, a collision avoidance component is added to the controller to guarantee that the agents do not collide. The new controller is shown to safely achieve coverage. Several numerical examples are provided to illustrate the main results.

关键词： collision avoidance cooperative systems coverage control mobile sensor systems multisensor systems sensor networks

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How to Systematically Distribute Candidate Models and Robust controllers in Multiple-Model Adaptive control: A coverage control Approach

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IEEE TRANSACTIONS ON AUTOMATIC control 2018年第4期63卷 1075-1089页

作者： Kersting, Stefan Buss, Martin Tech Univ Munich Inst Adv Study Chair Automat Control Engn D-80333 Munich Germany

Distributing nominal models in multiple-models applications constitutes a long standing problem. The set of models needs to be distributed in such a way that their corresponding controllers can stabilize all possible system configurations in a large uncertainty set. This paper presents a systematic solution by phrasing the distribution as coverage control problem, in which each model covers a subset of the uncertainty. The subsets are derived based on a combination of the v-gap metric, which serves as a distance measure, and the generalized stability margin. Characterizing coverage in terms of the v-gap also motivates the use of H-infinity controller synthesis to design a set of controllers. The proposed algorithms are initialized with suboptimal model configurations. Two update laws optimize the model parameters and minimize the coverage function. The first algorithm performs a gradient descent on the coverage function and the second algorithm performs pairwise optimizations. Due to computational complexity, a discretized implementation is derived, which reduces the optimization to an efficient graph search. The proposed algorithms are evaluated in numeric benchmark examples.

关键词： coverage control multiple model adaptive control (MMAC) robust control

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coverage control for Mobile Sensing Robots in Unknown Environments Using Neural Network

Coverage Control for Mobile Sensing Robots in Unknown Enviro...

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IEEE International Conference on control Applications Part of 2010 IEEE Multi-Conference on Systems and control

作者： Dirafzoon, A. Salehizadeh, S. M. A. Emrani, S. Menhaj, M. B. Afshar, A. Amir Kabir Univ Technol Dept Elect Engn Tehran Iran

ISBN: (纸本)9781424453610

This study proposes a distributed control algorithm for coverage in unknown environments with networked mobile sensors. The control law is derived according to the online neural network estimation of the sensory function of the environments. In contrary to previous adaptive approaches, a major advantage of the proposed method is that due to the neural network nonlinear approximation property, it is not restricted to multi Gaussian sensory functions. Simulation results show that the proposed controller outperforms the previous adaptive approaches in the sense of performance and convergence rate.

关键词： Gaussian processes approximation theory coverage control distributed control distributed control algorithm mobile robots mobile sensing robots multi Gaussian sensory functions networked mobile sensors neural network nonlinear approximation property neurocontrollers online neural network estimation sensors unknown environments

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Dynamic coverage control for Constrained Mobile Sensor Networks

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IEEE TRANSACTIONS ON AUTOMATIC control 2024年第4期69卷 2131-2142页

作者： Peng, Bowen Zhang, Zhirong Song, Yongduan Chongqing Univ Sch Automat Chongqing 400044 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore Chongqing Univ Chongqing Key Lab Intelligent Unmanned Syst Chongqing 400044 Peoples R China Chongqing Univ Star Inst Intelligent Syst Chongqing 400044 Peoples R China

In this article, we study the cooperative dynamic coverage control problem by using viability theory. We focus on the intertemporal coverage optimization for nonlinear mobile sensor networks with mobility constraint, arbitrary sensory range, and obstacle avoidance over large-scale domains, which remains to be an interesting open problem prior to this work. Our proposed cooperative coverage control law enables the constrained sensor networks to minimize the overall intertemporal cost of the distributed attention factors throughout the mission domain, while avoiding unforeseen obstacles, by just local information. The mobility constraint of the mobile sensors includes nonzero velocity and bounded turning rate, where the unforeseen obstacles, the mission domain, and the sensory range are considered to be arbitrary compact sets. The viable detection domain is proposed based on viability theory, which is the largest set of states within the sensory domain, and the designed control strategy enables the mobile sensor to detect any target point inside it in a finite time while avoiding obstacles. Effective algorithms capable of reconstructing the viable detection domain are derived, with which both the noncooperative and cooperative coverage control strategies are developed, and their corresponding coverage performances are analytically evaluated. The efficiency of the proposed method is confirmed and illustrated via simulations.

关键词： Capture basin collision avoidance constrained nonlinear systems cooperative control coverage control multiagent systems viability kernel viability theory

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Active Learning-Based Model Predictive coverage control

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IEEE TRANSACTIONS ON AUTOMATIC control 2024年第9期69卷 5931-5946页

作者： Rickenbach, Rahel Kohler, Johannes Scampicchio, Anna Zeilinger, Melanie N. Carron, Andrea Swiss Fed Inst Technol Inst Dynam Syst & Control CH-8092 Zurich Switzerland

The problem of coverage control, i.e., of coordinating multiple agents to optimally cover an area, arises in various applications. However, coverage applications face two major challenges: 1) dealing with nonlinear dynamics while respecting system and safety critical constraints and 2) performing the task in an initially unknown environment. We solve the coverage problem by using a hierarchical framework, in which references are calculated at a central server and passed to the agents' local model predictive control (MPC) tracking schemes. Furthermore, to ensure that the environment is actively explored by the agents a probabilistic exploration-exploitation tradeoff is deployed. In addition, we derive a control framework that avoids the hierarchical structure by integrating the reference optimization in the MPC formulation. Active learning is then performed drawing inspiration from Upper Confidence Bound (UCB) approaches. For all developed control architectures, we guarantee closed-loop constraint satisfaction and convergence to an optimal configuration. Furthermore, all methods are tested and compared on hardware using a miniature car platform.

关键词： Agents and autonomous systems cooperative control coverage control machine learning NL predictive control Agents and autonomous systems cooperative control coverage control machine learning NL predictive control

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Multivehicle coverage control for a nonstationary spatiotemporal field

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AUTOMATICA 2014年第5期50卷 1381-1390页

作者： Sydney, Nitin Paley, Derek A. Univ Maryland Dept Aerosp Engn College Pk MD 20742 USA Univ Maryland Syst Res Inst College Pk MD 20742 USA

This paper presents a multivehicle sampling algorithm to generate trajectories for nonuniform coverage of a nonstationary spatiotemporal field characterized by spatial and temporal decorrelation scales that vary in space and time, respectively. The sampling algorithm described in this paper uses a nonlinear coordinate transformation that renders the field locally stationary so that existing multivehicle control algorithms can be used to provide uniform coverage. When transformed back to the original coordinates, the sampling trajectories are concentrated in regions of short spatial and temporal decorrelation scales. For fields with coupled spatial statistics, i.e., the spatial decorrelation scales are functions of both spatial dimensions, the coordinate transformation is implemented numerically, whereas for decoupled spatial statistics, the transformation is expressed analytically. We show that the analytical transformation results in vehicle motion that preserves the vehicle sampling speed (which is a measure of vehicle speed scaled by the ratio of the spatial and temporal decorrelation scales), in the original domain;the sampling speed determines the minimum number of vehicles needed to cover a spatiotemporal domain. Theoretical results are illustrated by numerical simulations. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Adaptive sampling Nonlinear control Nonstationary fields coverage control

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Finite-Time coverage control for Multiagent Systems With Unidirectional Motion on a Closed Curve

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IEEE TRANSACTIONS ON CYBERNETICS 2021年第6期51卷 3071-3078页

作者： Song, Cheng Fan, Yuan Xu, Shengyuan Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Anhui Univ Sch Elect Engn & Automat Hefei 230601 Peoples R China

The finite-time coverage control problem for networked mobile agents with continuous-time dynamics and unidirectional motion constraint on a closed curve is addressed in this article. The objective is to minimize a coverage cost function in finite time which characterizes the largest arrival time from the multiagent system to any point on the curve. Low gain feedback is employed to design the distributed coverage control laws for the agents with different input constraints due to their limited movement capabilities. An upper bound on each low gain is also provided by showing that the distance between the neighboring agents is always lower and upper bounded. Under the proposed control laws, the networked mobile agents can be driven to the optimal configuration, minimizing the coverage cost function in finite time. Due to the unidirectional motion of the agents, there exists at least one agent which remains static throughout the coverage task. As a result, a less conservative upper bound on the low gains is derived, which provides the possibility of better convergence rates of the proposed coverage control laws.

关键词： Mobile agents Multi-agent systems Cost function Upper bound Robot sensing systems Time factors coverage control distributed control finite-time convergence multiagent systems

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Efficient angle-aware coverage control for large-scale 3D map reconstruction using drone networks

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SICE JOURNAL OF control MEASUREMENT AND SYSTEM INTEGRATION 2024年第1期17卷 144-155页

作者： Hanif, Muhammad Shimizu, Takumi Lu, Zhiyuan Suenaga, Masaya Hatanaka, Takeshi Tokyo Inst Technol 2-12-1 OokayamaMeguro Ku Tokyo 1528550 Japan

This paper presents a novel angle-aware coverage control method to enhance monitoring efficiency for large-scale 3D map reconstruction using drone networks. The proposed method integrates a Voronoi-based coverage control as the nominal input into the quadratic programming problem required to solve in the original angle-aware coverage control. This approach provides a practical solution, ensuring diverse viewing angles to improve the quality of 3D map reconstruction and offers effective coverage of distant unobserved areas, particularly for large-scale area missions. We then implement the present method and validate its effectiveness through simulation on Robot Operating System as well as experiments conducted on a robotic testbed. The comparative analysis demonstrates the advantages of our proposed approach, resulting in increased monitoring efficiency for large-scale 3D map reconstruction.

关键词： Multi-robot systems coverage control control barrier function quadratic programming-based control 3D map reconstruction drone networks

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Angle-Aware coverage control for 3-D Map Reconstruction With Drone Networks

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IEEE control SYSTEMS LETTERS 2022年 6卷 1831-1836页

作者： Shimizu, Takumi Yamashita, Shunya Hatanaka, Takeshi Uto, Kuniaki Mammarella, Martina Dabbene, Fabrizio Tokyo Inst Technol Sch Engn Tokyo 1528552 Japan Tokyo Inst Technol Sch Comp Tokyo 1528552 Japan Politecn Torino Inst Elect Comp & Telecommun Engn I-10129 Turin Italy

In this letter, we address environmental monitoring for 3-D map reconstruction using drone networks. In view of the fact that the 3-D reconstruction requires images from a variety of viewing angles, we first formulate a novel angle-aware coverage control problem, based on a concept of virtual field that combines the position of a monitoring target and the viewing angle. Then, we define an objective function with an importance index, updated according to the history of the past coverage states. In the present scenario, drones are required not only to minimize the objective function but also to take situation-adaptive actions, e.g., a drone should quickly escape a region having low importance indices. To this end, we design a QP-based controller that switches actions depending on the current importance index. We finally demonstrate the effectiveness of the presented controller through simulations on Robot Operating System.

关键词： Drones Monitoring Indexes Image reconstruction Linear programming Standards Sensors Multi-robot systems coverage control quadratic programming-based control map reconstruction

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Development of global optimal coverage control using multiple aerial robots

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ADVANCED ROBOTICS 2019年第19期33卷 996-1005页

作者： Shibata, K. Miyano, T. Jimbo, T. Toyota Cent Res & Dev Labs Inc Appl Math Res Domain Autonomous Distributed Cooperat Control Program 41-1 Yokomichi Nagakute Aichi 4801192 Japan

coverage control has been widely used for constructing mobile sensor network such as for environmental monitoring, and one of the most commonly used methods is the Lloyd algorithm based on Voronoi partitions. However, when this method is used, the result sometimes converges to a local optimum. To overcome this problem, game theoretic coverage control has been proposed and found to be capable of stochastically deriving the optimal deployment. From a practical point of view, however, it is necessary to make the result converge to the global optimum deterministically. In this paper, we propose a global optimal coverage control along with collision avoidance in continuous space that ensures multiple sensors can deterministically and smoothly move to the global optimal deployment. This approach consists of a cut-in algorithm based on neighborhood importance of measurement and a modified potential method for collision avoidance. The effectiveness of the proposed algorithm has been confirmed through numerous simulations and some experiments using multiple aerial robots.

关键词： Distributed control coverage control aerial robot mobile sensor

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