scholarly journals Behavior-based Navigation of Mobile Robot in Unknown Environments Using Fuzzy Logic and Multi-Objective Optimization

2017 ◽  
Vol 10 (2) ◽  
pp. 349-364 ◽  
Author(s):  
Thi Thanh Van Nguyen ◽  
Manh Duong Phung ◽  
Quang Vinh Tran
Author(s):  
Đào Thị Làn ◽  
Nguyen Thi Thanh Van ◽  
Phung Manh Duong ◽  
Dang Anh Viet ◽  
Tran Quang Vinh

Abstract: This study proposes behavior-based navigation architecture, named BBFM, for mobile robot in unknown environment with obstacles. The architecture is carried out in three steps: (i) analyzing the navigation problem to determine parameters of the architecture; (ii) designing the objective functions to relate input data with the desired output; and (iii) fusing the output of each objective function to generate the optimal control signal. We use fuzzy logic to design the objective functions and multi-objective optimization to find the Pareto optimal solution for the fusion. A number of simulations, comparisons, and experiments were conducted. The results show that the proposed architecture outperforms some popular behavior- based architectures in navigating the mobile robot in complex environments. Keywords: Behavior-based navigation, fuzzy logic, multi-objective optimization, mobile robot.


2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Hongwei Mo ◽  
Qirong Tang ◽  
Longlong Meng

A new behavior-based fuzzy control method for mobile robot navigation is presented. It is based on behavioral architecture which can deal with uncertainties in unknown environments and has the ability to accommodate different behaviors. Basic behaviors are controlled by specific fuzzy logic controllers, respectively. The proposed approach qualifies for driving a robot to reach a target while avoiding obstacles in the environment. Simulation and experiments are performed to verify the correctness and feasibility of the proposed method.


2019 ◽  
Vol 236 ◽  
pp. 117711 ◽  
Author(s):  
R. Kumar ◽  
N. Rajesh Jesudoss Hynes ◽  
Catalin Iulian Pruncu ◽  
J. Angela Jennifa Sujana

2001 ◽  
Vol 124 (1) ◽  
pp. 77-82 ◽  
Author(s):  
S. Conti ◽  
G. Tina ◽  
C. Ragusa

In this paper, an automatic procedure to perform the optimal sizing of a stand-alone solar electrical system with battery storage is developed by a fuzzy logic based multi-objective optimization approach. The procedure aims at finding the configuration that yields the best compromise for the two considered objectives: the long-term average performance and the overall cost of the generating system. In particular, the objectives of the optimization problem are: the maximization of the Supplied Load Fraction, that is the fraction of the actual electrical load that can be supplied by the system, and the minimization of the Relative Unit Electricity Cost, that is the net cost of generating each kWh during the lifetime of the stand-alone solar electrical system referred to the UEC calculated in case of loads supplied by the grid. The control variables are the solar cell array surface, the tilt angle of the modules, and the storage system capacity. The fuzzy multi-objective optimization procedure is described and the application results are presented considering different configurations characterized by some parameters, such as the electrical load, the yearly power demand, the distance from the utility grid, and the solar cells unit cost.


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