A Sparse Branch and Bound Optimization of Noisy Weighted DAG Modification under Constraints: A Method for Monocular Data Association to Multiple Laser Planes

Automated Guided Vehicle (AGV) indoor autonomous cargo handling and commodity transportation are inseparable from AGV autonomous navigation, and positioning and navigation in an unknown environment are the keys of AGV technology. In this paper, the extended Kalman filter algorithm is used to match the sensor observations with the existing features in the map to determine the accurate positioning of the AGV. This paper proposes an improved joint compatibility branch and bound (JCBB) method to divide the data and then randomly extract part of the data in the divided data set, thereby reducing the data association space; then, the JCBB algorithm is used to perform data association and finally merge the associated data. This method can solve the problem of the increased computational complexity of JCBB when the amount of data to be matched is large to achieve the effect of increasing the correlation speed and not reducing the accuracy rate, thereby ensuring the real-time positioning of the AGV.

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Optimasi keuntungan dengan metode Branch and Bound

AKSIOMA ◽

10.26877/aks.v10i1.3145 ◽

2019 ◽

Vol 10 (1) ◽

pp. 13-23

Author(s):

Sri Siti Supatimah ◽

Farida Farida ◽

Siska Andriani

Keyword(s):

Linear Programming ◽

Branch And Bound ◽

Integer Linear Programming ◽

Limited Resources ◽

Decision Variable ◽

City Community ◽

Maximum Profit ◽

The Right ◽

The City ◽

Bound Optimization

Sentral Me Laundry is one of the service services businesses established in 2016 and has 2 employees having their address at Jalan pulau Ambon, Sukarame, Bandar Lampung. The development of laundry services in the middle of the city community indicates that laundry businesses can still develop and can achieve optimal profits. The purpose of this study was to find the optimal benefits obtained by the Sentral Me Laundry business. Errors in planning a laundry business result in a maximum profit. To prevent mistakes in planning a laundry business, it is necessary to use the right method. Banch And Bound Method (Integer Linear Programming) is a method that can be used to optimize laundry business by looking at the limited resources of the business. In the linear program method the decision variable can be a real number. While the optimization of laundry business that will be done requires a solution in the form of an integer called Integer. To help resolve cases of optimizing the benefits of laundry businesses using a computer program, QM For Windows. Calculations from the QM For Windows program produce 53 Kg of Badcover, 188 Kg of Doll, 1350 Kg of Clothing, 101 Kg of Blanket.. Keywords: Branch and Bound; Optimization; QM For Windows

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Branch-and-Bound Optimization of a Multiagent System for Flow Production using Model Checking

Proceedings of the 8th International Conference on Agents and Artificial Intelligence ◽

10.5220/0005705100270037 ◽

2016 ◽

Cited By ~ 1

Author(s):

Stefan Edelkamp ◽

Christoph Greulich

Keyword(s):

Model Checking ◽

Branch And Bound ◽

Multiagent System ◽

Bound Optimization

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A Data Association Algorithm for SLAM Based on Central Difference Joint Compatibility Criterion and Clustering

Robotica ◽

10.1017/s0263574720001435 ◽

2021 ◽

pp. 1-18

Author(s):

Dan Liu

Keyword(s):

Computational Complexity ◽

Mobile Robot ◽

Branch And Bound ◽

Mahalanobis Distance ◽

Data Association ◽

Branch And Bound Method ◽

Simulation Data ◽

Central Difference ◽

Localization And Mapping ◽

Association Algorithm

SUMMARY A data association algorithm for simultaneous localization and mapping (SLAM) based on central difference joint compatibility (CDJC) criterion and clustering is proposed to obtain the data association results. Firstly, CDJC criterion is designed to calculate joint Mahalanobis distance. Secondly, ordering points to identify the clustering structure is used to divide all observed features into several groups. Thirdly, CDJC branch and bound method is designed to be performed in each group. The results based on simulation data and benchmark dataset show that the proposed algorithm has low computational complexity and provide accurate association results for SLAM of mobile robot.

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