scholarly journals Multi-Robot Indoor Environment Map Building Based on Multi-Stage Optimization Method

2021 ◽  
Vol 1 (2) ◽  
pp. 145-161
Author(s):  
Hui Lu ◽  
Siyi Yang ◽  
Meng Zhao ◽  
Shi Cheng
Keyword(s):  
Indoor Environment ◽  
Optimization Method ◽  
Map Building ◽  
Environment Map ◽  
Multi Stage ◽  
Multi Robot

scholarly journals Kinect-based 3D Indoor Environment Map Building

2017 ◽  
Author(s):  
Yi ZHANG ◽  
Qi CHEN ◽  
Xiao-Lin ZHONG ◽  
Qiao-Zhen LIAO
Keyword(s):  
Indoor Environment ◽  
Map Building ◽  
Environment Map

Map Building in Indoor Environment for Service Robot Based on Laser Sensor

2012 ◽  
Vol 461 ◽  
pp. 671-676
Author(s):  
Long Hui Wu ◽  
Shi Gang Cui ◽  
Li Zhao
Keyword(s):  
Autonomous Navigation ◽  
Indoor Environment ◽  
Service Robot ◽  
Laser Sensor ◽  
Uncertain Information ◽  
Map Building ◽  
Environment Map ◽  
Map Updating ◽  
Fitting In ◽  
Local Map

Map building is an essential problem in the field of mobile robot research. The accurate environmental map provides the important safeguard for the robot autonomous navigation and localization. In this paper, the two-dimensional environment map based on geometric features information was built by laser data when service robot worked in indoor structured environment. However, this article focused on analyzing the method of line fitting in the process of building local map and the method of global map updating. The experiment indicated that this method has the high accuracy and effectiveness, also reduces error caused by the uncertain information in the process of map building, which makes the indoor environment map update in real time.

A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition for corporate bankruptcy prediction

2020 ◽  
pp. 1-17
Author(s):  
Dongqi Yang ◽  
Wenyu Zhang ◽  
Xin Wu ◽  
Jose H. Ablanedo-Rosas ◽  
Lingxiao Yang ◽  
...  
Keyword(s):  
Fuzzy Clustering ◽  
Rapid Development ◽  
Optimization Method ◽  
Selection Method ◽  
Bankruptcy Prediction ◽  
Ensemble Model ◽  
Composition Method ◽  
Classifier Selection ◽  
Multi Stage ◽  
Proposed Model

With the rapid development of commercial credit mechanisms, credit funds have become fundamental in promoting the development of manufacturing corporations. However, large-scale, imbalanced credit application information poses a challenge to accurate bankruptcy predictions. A novel multi-stage ensemble model with fuzzy clustering and optimized classifier composition is proposed herein by combining the fuzzy clustering-based classifier selection method, the random subspace (RS)-based classifier composition method, and the genetic algorithm (GA)-based classifier compositional optimization method to achieve accuracy in predicting bankruptcy among corporates. To overcome the inherent inflexibility of traditional hard clustering methods, a new fuzzy clustering-based classifier selection method is proposed based on the mini-batch k-means algorithm to obtain the best performing base classifiers for generating classifier compositions. The RS-based classifier composition method was applied to enhance the robustness of candidate classifier compositions by randomly selecting several subspaces in the original feature space. The GA-based classifier compositional optimization method was applied to optimize the parameters of the promising classifier composition through the iterative mechanism of the GA. Finally, six datasets collected from the real world were tested with four evaluation indicators to assess the performance of the proposed model. The experimental results showed that the proposed model outperformed the benchmark models with higher predictive accuracy and efficiency.

DISTRIBUTION INCENTIVE SYSTEM FOR ELECTRICAL COMPANIES

2021 ◽  
Vol 4 (5) ◽  
pp. 43-48
Author(s):  
Yu. V. NIKITOCHKINA ◽  
Keyword(s):  
Optimization Method ◽  
Incentive System ◽  
New Model ◽  
Incentive Model ◽  
Multi Stage ◽  
Commercial Enterprise ◽  
Product Image

This article proposes a new model for stimulating distributors – a multi-stage scale that compares the distributor's rating with the percentage level of discount for regional coverage and specialization. The list of indicators for calculating discounts by specialization and regional coverage includes a group of indicators to increase the motivation of the distributor to improve the quality of their work and a group of indicators to increase the motivation of the distributor to expand the scope of action. Using the method of index grouping of expert estimates, the weight values of each indicator were found. The task of calculating the evaluation of the results of the distribution was set as a multi-criteria task, in which the additive optimization method was used for the procedure of folding private criteria, which was preceded by checking all private criteria for addi-tive independence. The developed incentive model can be adapted for any commercial enterprise interested in promoting its product through regional coverage, as well as in supporting the product image, which, of course, contributes to stimulating demand and increasing sales.

Multi-robot exploration for search and rescue missions: A report of map building in RoboCupRescue 2009

2009 ◽  
Author(s):  
Keiji Nagatani ◽  
Yoshito Okada ◽  
Naoki Tokunaga ◽  
Kazuya Yoshida ◽  
Seiga Kiribayashi ◽  
...  
Keyword(s):  
Search And Rescue ◽  
Map Building ◽  
Multi Robot

scholarly journals Review of Vision-Based Robot Navigation Method

2015 ◽  
Vol 4 (4) ◽  
pp. 254
Author(s):  
Budi Rahmani ◽  
Agfianto Eko Putra ◽  
Agus Harjoko ◽  
Tri Kuntoro Priyambodo
Keyword(s):  
Robot Navigation ◽  
Map Building ◽  
Environment Map ◽  
Research Theme ◽  
Navigation Method

Vision-based robot navigation is a research theme that continues to be developed up to now by the researchers in the field of robotics. There are innumerable methods or algorithms are developed, and this paper described the reviews of the methods. The methods are distinguished whether  the robot is equipped with the navigation map (map-based), the map is built incrementally as robot observes the environment (map-building), or the robot navigates using no map (mapless). In this paper will described navigation methods of map-based, map-building, and mapless category.

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