scholarly journals Optimal Deployment of Camera Mounted UAVs Performing Search

2018 ◽  
Vol 7 (2.21) ◽  
pp. 161
Author(s):  
Jeane Marina D’Souza ◽  
Siddhartha Suresh Rao ◽  
K R. Guruprasad
Keyword(s):  
Density Distribution ◽  
Voronoi Cell ◽  
Uncertainty Reduction ◽  
Deployment Strategy ◽  
Search Area ◽  
Multiple Uavs ◽  
Lack Of Information ◽  
Optimal Deployment ◽  
Simulation Results ◽  
Multi Robot

In this paper we address a problem of optimal deployment of camera mounted UAVs for a multi-robot search application. Here   multiple UAVs carrying downward facing cameras are required to look for targets of interest in a search area. The lack of information about the presence or absence of targets is modeled as an uncertainty density distribution over the search area and this uncertainty is reduced as the information is gathered using the onboard cameras. The UAVs are required to get deployed so as to maximize the uncertainty reduction. We provide a model for search effectiveness of the camera and use it to formulate a strategy for optimal deployment of UAVs. It is shown that a centroidal Voronoi configuration, where each UAV (camera) is located at the centroid of the corresponding Voronoi cell is an optimal deployment. We provide simulation results to demonstrate that the proposed optimal deployment strategy successfully      deploys the UAVs into centroidal Voronoi configuration, which maximizes the uncertainty reduction using cameras as search sensors.  

scholarly journals A Sensor Deployment Approach Using Improved Virtual Force Algorithm Based on Area Intensity for Multisensor Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Jiahao Xie ◽  
Daozhi Wei ◽  
Shucai Huang ◽  
Xiangwei Bu
Keyword(s):  
Sensor Deployment ◽  
Local Optimum ◽  
Detection Model ◽  
Coverage Optimization ◽  
Virtual Force ◽  
Global Coverage ◽  
Optimal Deployment ◽  
Coverage Quality ◽  
Simulation Results ◽  
Sensor Detection

Sensor deployment is one of the major concerns in multisensor networks. This paper proposes a sensor deployment approach using improved virtual force algorithm based on area intensity for multisensor networks to realize the optimal deployment of multisensor and obtain better coverage effect. Due to the real-time sensor detection model, the algorithm uses the intensity of sensor area to select the optimal deployment distance. In order to verify the effectiveness of this algorithm to improve coverage quality, VFA and PSOA are selected for comparative analysis. The simulation results show that the algorithm can achieve global coverage optimization better and improve the performance of virtual force algorithm. It avoids the unstable coverage caused by the large amount of computation, slow convergence speed, and easily falling into local optimum, which provides a new idea for multisensor deployment.

Simulation of Market Price Formation as a Game Between Stochastic Automata

1976 ◽  
Vol 98 (1) ◽  
pp. 91-100 ◽  
Author(s):  
Y. M. El-Fattah ◽  
R. Henriksen
Keyword(s):  
Conditional Probability ◽  
A Priori ◽  
Market Price ◽  
Competitive Market ◽  
Price Formation ◽  
Market Conditions ◽  
Reinforcement Scheme ◽  
Stochastic Automata ◽  
Lack Of Information ◽  
Simulation Results

A seller in a free competitive market attempts to optimize his profit by manipulating the price of his commodity. A seller does not know a priori the market conditions such as the conditional probability of the buyers demand, the criteria or even the number of his seller opponents. Subject to this lack of information, the process of market price formation can be simulated as a game between stochastic automata. As time unfolds each seller-automaton learns the market conditions and changes accordingly its price probabilities in view of maximizing its profit. A simple reinforcement scheme is introduced for the design of such automata. The simulation results demonstrate the expediency of the automata behavior.

A new modifier adaptation methodology for real-time optimization

2017 ◽  
Vol 40 (4) ◽  
pp. 1320-1327
Author(s):  
Chunhua Chen ◽  
Mingxing Jia ◽  
Fuqiang You ◽  
Fuli Wang ◽  
Wenqi Kou
Keyword(s):  
Real Time ◽  
Flue Gas ◽  
Optimization Problem ◽  
Gradient Estimation ◽  
Search Area ◽  
Time Optimization ◽  
Decision Variables ◽  
Optimal Setting ◽  
Simulation Results ◽  
Real Time Optimization

The traditional modifier adaptation can be used to deal with the optimization problem of mismatched model, and it shows good performance in most cases. However, the method cannot be used directly, when the gradients of the model outputs, with respect to the decision variables, are difficult to calculate directly. Also, the simulation results show that the method cannot achieve the optimum in theory when the gradient estimation is particularly inaccurate. Therefore, a new modifier adaptation methodology for real-time optimization is proposed in this paper. A method similar to Proportion integration differentiation is used to deal with the deviation between the actual gradient and the model gradient and to improve the method of modifier terms computation. In addition, we find that the appropriate relaxation of certain constraints can expand the search area and improve the effectiveness of the optimization. The validation of the method is demonstrated by the solution of an artificial example and the optimal setting problem of the converter entrance temperatures in flue gas acid-making.

Optimal Deployment for Mobile Target Tracking in Sensor Networks

2012 ◽  
Vol 468-471 ◽  
pp. 1657-1660
Author(s):  
Ying Chi Mao
Keyword(s):  
Target Tracking ◽  
Tracking Performance ◽  
Wireless Sensor ◽  
Sensor Deployment ◽  
Surveillance Systems ◽  
Challenging Problem ◽  
Irregular Pattern ◽  
Optimal Deployment ◽  
Mobile Target ◽  
Simulation Results

Mobile target tracking is a key application of wireless sensor network-based surveillance systems. Sensor deployment is an important factor in tracking performance and remains a challenging problem. In this paper, we address the problem of optimal sensor deployment for mobile target tracking. We analyze the tracking performance of three patterns. Simulation results demonstrate that the irregular pattern outperforms the other two patterns.

scholarly journals Strategies for Optimal Deployment of Related Clones into Seed Orchards

2008 ◽  
Vol 57 (1-6) ◽  
pp. 119-127 ◽  
Author(s):  
D. Danusevičius ◽  
D. Lindgren
Keyword(s):  
Gene Diversity ◽  
Seed Orchard ◽  
Breeding Values ◽  
Truncation Selection ◽  
Deployment Strategy ◽  
Ranking Criteria ◽  
The Status ◽  
Sib Families ◽  
Optimal Deployment ◽  
Status Number

Abstract This study deals with how the deployed proportion of each candidate clone can be decided at the establishment of a seed orchard when the breeding values are available for each candidate in a population of unrelated half-sib families. The following deployment strategies were compared: (a) truncation selection by selecting the clones with the breeding values exceeding certain threshold and deploying equal number of ramets (Truncation strategy); (b) truncation selection by selecting only one best individual within each family (Truncation unrelated); (c) maximizing gain at a given effective clone number (Linear deployment); (d) linear deployment by selecting one best individual within each family (Linear deployment unrelated) and (e) maximizing net gain at a given gene diversity (Optimal proportions). The study focused on the latest alternative and described its superiority and characteristics for a number of possible typical cases. The genetic gain adjusted for predicted inbreeding depression (Net gain), gene diversity and effective clone number were considered as the main ranking criteria. The strategies optimizing the number of related individuals and the linear deployment strategy with restriction on relatedness returned the highest Net gain. If there is a large diversity to select from (the status number of the candidates is more than 8 times greater than the status number desired in the seed orchard), a relatively simple advice is to select the best individual within the best families and deploy the clones linearly according to their breeding values (the number of families selected depends on the desired status number). If the diversity available to select from is small, it seems recommendable to allow half-sibs among the selections and use the Optimal proportions deployment strategy. As the breeding cycles proceed, the status number of the candidate population will decrease and the Optimal proportions strategy is likely to become more favorable.

scholarly journals Consensus in networked multi-robot systems via local state feedback robust control

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989354
Author(s):  
Shijie Zhang ◽  
Yi Cao
Keyword(s):  
State Feedback ◽  
Dynamical Equation ◽  
Local Information ◽  
Network Graph ◽  
Robust Controller ◽  
Common Value ◽  
Robot Systems ◽  
Simulation Results ◽  
The Individual ◽  
Multi Robot

In the article, the consensus problem is considered for networked multi-robot systems, in which the dynamical equation of all robots is non-holonomic and nonlinear systems. In the multi-robot systems, each robot updates its current states and receives the states from the neighboring robots. Under the assumption that if the network graph is bidirectional, a local information-based state feedback robust controller is designed to make sure the convergence of the individual robots’ states to a common value. Finally, the effectiveness of the presented method is illustrated by the simulation results of a group of four mobile robots.

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