Decentralized control for mobile robotic sensor network self-deployment: barrier and sweep coverage problems

Robotica ◽  
2010 ◽  
Vol 29 (2) ◽  
pp. 283-294 ◽  
Author(s):  
Teddy M. Cheng ◽  
Andrey V. Savkin
Keyword(s):  
Sensor Network ◽  
Decentralized Control ◽  
Nearest Neighbor ◽  
Barrier Coverage ◽  
Control Law ◽  
Motion Coordination ◽  
Robotic Sensor ◽  
Information Consensus ◽  
Coverage Problems ◽  
Robotic Sensors

SUMMARYThis paper addresses the problems of barrier coverage and sweep coverage in a corridor environment with a network of self-deployed mobile autonomous robotic sensors. Using the ideas of nearest neighbor rules and information consensus, we propose a decentralized control law for the robotic sensors to solve the coverage problems. Numerical simulations illustrate the effectiveness of the proposed algorithm. The results in this paper demonstrate that such simple motion coordination rules can play a significant role in addressing the issue of coverage in a mobile robotic sensor network.

Self-deployment of mobile robotic sensor networks for multilevel barrier coverage

Robotica ◽  
2011 ◽  
Vol 30 (4) ◽  
pp. 661-669 ◽  
Author(s):  
Teddy M. Cheng ◽  
Andrey V. Savkin
Keyword(s):  
Sensor Networks ◽  
Numerical Simulations ◽  
Local Information ◽  
Barrier Coverage ◽  
Coverage Problem ◽  
Decentralized Coordination ◽  
Robotic Sensor ◽  
Simple Rules ◽  
Robotic Sensor Networks ◽  
Robotic Sensors

SUMMARYWe study a problem of K-barrier coverage by employing a network of self-deployed, autonomous mobile robotic sensors. A decentralized coordination algorithm is proposed for the robotic sensors to address the coverage problem. The algorithm is developed based on some simple rules that only rely on local information. By applying the algorithm to the robotic sensors, K layers of sensor barriers are formed to cover the region between two given points. To illustrate the proposed algorithm, numerical simulations are carried out for a number of scenarios.

scholarly journals Energy-efficient non-linear k-barrier coverage in mobile sensor network

2020 ◽  
Vol 17 (3) ◽  
pp. 737-758
Author(s):  
Zijing Ma ◽  
Shuangjuan Li ◽  
Longkun Guo ◽  
Guohua Wang
Keyword(s):  
Sensor Network ◽  
Mobile Sensors ◽  
Barrier Coverage ◽  
Force Model ◽  
Mobile Sensor ◽  
Mobile Sensor Network ◽  
Virtual Force ◽  
Straight Line ◽  
Non Linear ◽  
Single Sensor

K-barrier coverage is an important coverage model for achieving robust barrier coverage in wireless sensor networks. After initial random sensor deployment, k-barrier coverage can be achieved by moving mobile sensors to form k barriers consisting of k sensor chains crossing the region. In mobile sensor network, it is challenging to reduce the moving distances of mobile sensors to prolong the network lifetime. Existing work mostly focused on forming linear barriers, that is the final positions of sensors are on a straight line, which resulted in large redundant movements. However, the moving cost of sensors can be further reduced if nonlinear barriers are allowed, which means that sensors? final positions need not be on a straight line. In this paper, we propose two algorithms of forming non-linear k barriers energy-efficiently. The algorithms use a novel model, called horizontal virtual force model, which considers both the euclidean distance and horizontal angle between two sensors. Then we propose two barrier forming algorithms. To construct a barrier, one algorithm always chooses the mobile sensor chain with the largest horizontal virtual force and then flattens it, called sensor chain algorithm. The other chooses the mobile sensor with the largest horizontal virtual force to construct the barrier, other than the mobile sensor chain, called single sensor algorithm. Simulation results show that the algorithms significantly reduce the movements of mobile sensors compared to a linear k-barrier coverage algorithm. Besides, the sensor chain algorithm outperforms the single sensor algorithm when the sensor density becomes higher.

INVESTIGATING A WIRELESS SENSOR NETWORK OPTIMAL LIFETIME SOLUTION FOR LINEAR TOPOLOGIES

2006 ◽  
Vol 07 (01) ◽  
pp. 91-99 ◽  
Author(s):  
Keith Hellman ◽  
Michael Colagrosso
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Nearest Neighbor ◽  
Analytic Solution ◽  
Routing Algorithm ◽  
Optimal Solution ◽  
Routing Algorithms ◽  
Wireless Sensor ◽  
Global Knowledge ◽  
Alternative Solutions

We investigate a known optimal lifetime solution for a linear wireless sensor network through simulation, and propose alternative solutions where a known optimal solution does not exist. The network is heterogeneous in the sensors' energy distribution and also in the amount of data each sensor must communicate. As a basis for comparison, we analyze the lifetime of a network using a simple, nearest-neighbor routing algorithm, and an analytic solution to the optimal lifetime of networks meeting certain constraints. Alternative solutions considered range from those requiring global knowledge of the network to solutions using only next-neighbor knowledge. We compare the performance of all the routing algorithms in simulation.

Decentralized Exergy/Entropy Thermodynamic Control for Collective Robotic Systems

2007 ◽  
Author(s):  
Rush D. Robinett ◽  
David G. Wilson
Keyword(s):  
Decentralized Control ◽  
Direct Method ◽  
Robotic Systems ◽  
Control Law ◽  
Thermodynamic Control ◽  
Order Accuracy ◽  
Control Laws ◽  
Vector Lyapunov Function ◽  
Collective Control ◽  
Plume Tracing

This paper develops a distributed decentralized control law for collective robotic systems. The control laws are developed based on exergy/entropy thermodynamic concepts and information theory. The source field is characterized through second-order accuracy. The proposed feedback control law stability for both the collective and individual robots are demonstrated by selecting a general Hamiltonian based solution developed as Fisher Information Equivalency as the vector Lyapunov function. Stability boundaries and system performance are then determined with Lyapunov’s direct method. A robot collective plume tracing numerical simulation example demonstrates this decentralized exergy/entropy collective control architecture.

Region Coverage and Protection with Sensors

2010 ◽  
pp. 63-78 ◽  
Author(s):  
Ted Brown ◽  
Peter Brass ◽  
Matthew P. Johnson ◽  
Simon Shamoun
Keyword(s):  
Intrusion Detection ◽  
Research Area ◽  
Barrier Coverage ◽  
Complete Coverage ◽  
Partial Coverage ◽  
Security Applications ◽  
Active Research ◽  
Coverage Problems ◽  
Hostile Environments ◽  
Active Research Area

Covering an area with sensors has been an active research area in recent years. Coverage problems for sensors include the positioning of the sensors in order to cover much or all of a region, once or many times, and using sensors whose coverage abilities vary. Certain problem extensions arise in security applications and when sensors are deployed in hostile environments: it may not be possible to safely enter the area, in which case sensors may be distributed randomly from a distance; even if the positions can be chosen, there may be some minimal placement error which must be compensated for; it may not be possible to provide complete coverage, in which case we may settle for partial coverage or only barrier coverage and position sensors for improved intrusion detection. Another factor to consider when parties are acting in a coalition is that differing types of sensors may be deployed by the different parties, which must be taken into account when choosing positions. This short survey deals with some recent results that are especially applicable to such settings.

scholarly journals Distributed Synchronization Control to Trajectory Tracking of Multiple Robot Manipulators

2011 ◽  
Vol 2011 ◽  
pp. 1-10 ◽  
Author(s):  
Yassine Bouteraa ◽  
Jawhar Ghommam ◽  
Gérard Poisson ◽  
Nabil Derbel
Keyword(s):  
Decentralized Control ◽  
Information Exchange ◽  
Robot Manipulators ◽  
Direct Method ◽  
Functional Method ◽  
Consensus Algorithm ◽  
Adaptive Synchronization ◽  
Synchronization Control ◽  
Control Law ◽  
Parameter Uncertainties

This paper investigates the issue of designing decentralized control laws to cooperatively command a team of general fully actuated manipulators. The purpose is to synchronize their movements while tracking a common desired trajectory. Based on the well-known consensus algorithm, the control strategy consists in synchronizing the joint position and the velocity of each robot in the network with respect to neighboring robots' joints and velocities. Modeled by an undirected graph, the cooperative robot network requires just local neighbor-to-neighbor information exchange between manipulators. So, it does not assume the existence of an explicit leader in the team. Based above all on combination of Lyapunov direct method and cross-coupling strategy, the proposed decentralized control law is extended to an adaptive synchronization control taking into account parameter uncertainties. To address the time delay problems in the network communication channels, the suggested synchronization control law robustly synchronizes robots to track a given trajectory. To this end, Krasovskii functional method has been used to deal with the delay-dependent stability problem. A real-time software simulator is developed to visualize the robot manipulators coordination.

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