1993 ◽  
Vol 59 (563) ◽  
pp. 1968-1975
Author(s):  
Toshihiko Kanbara ◽  
Jun Miura ◽  
Yoshiaki Shirai ◽  
Minoru Asada

2011 ◽  
Vol 403-408 ◽  
pp. 4777-4785
Author(s):  
Singh Mukesh Kumar ◽  
Mishra Deepak Kumar ◽  
R. Parhi Dayal ◽  
Singh Mahendra Prasad

This paper is related to the human perception based idea by using heuristic information for the navigation of mobile robots in cluttered dynamic environments which provides a general, robust, safe and optimized path. The heuristic rule base network consists of a simple algorithm which makes predefined estimation function very smaller. The estimation function should be adequately defined for desired movement in the environments. A navigation system using rule based technique that allows a mobile robot to travel in an environment about, which the robot has no prior knowledge. This heuristic rule is applied in conjunction with artificial neural network. The proposed intelligent controller provides an optimum trajectory which increases the effectiveness of a mobile robot. A series of simulations test has been conducted to show the effectiveness of the proposed algorithm.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Per Hilletofth ◽  
Movin Sequeira ◽  
Wendy Tate

PurposeThis paper investigates the suitability of fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.Design/methodology/approachTwo fuzzy-logic-based support tools are developed together with experts from a Swedish manufacturing firm. The first uses a complete rule base and the second a reduced rule base. Sixteen inference settings are used in both of the support tools.FindingsThe findings show that fuzzy-logic-based support tools are suitable for initial screening of manufacturing reshoring decisions. The developed support tools are capable of suggesting whether a reshoring decision should be further evaluated or not, based on six primary competitiveness criteria. In contrast to existing literature this research shows that it does not matter whether a complete or reduced rule base is used when it comes to accuracy. The developed support tools perform similarly with no statistically significant differences. However, since the interpretability is much higher when a reduced rule base is used and it require fewer resources to develop, the second tool is more preferable for initial screening purposes.Research limitations/implicationsThe developed support tools are implemented at a primary-criteria level and to make them more applicable, they should also include the sub-criteria level. The support tools should also be expanded to not only consider competitiveness criteria, but also other criteria related to availability of resources and strategic orientation of the firm. This requires further research with regard to multi-stage architecture and automatic generation of fuzzy rules in the manufacturing reshoring domain.Practical implicationsThe support tools help managers to invest their scarce time on the most promising reshoring projects and to make timely and resilient decisions by taking a holistic perspective on competitiveness. Practitioners are advised to choose the type of support tool based on the available data.Originality/valueThere is a general lack of decision support tools in the manufacturing reshoring domain. This paper addresses the gap by developing fuzzy-logic-based support tools for initial screening of manufacturing reshoring decisions.


2007 ◽  
Vol 2007 (0) ◽  
pp. _2A2-B10_1-_2A2-B10_2
Author(s):  
Kentaro TAKEMURA ◽  
Tsuyoshi SUENAGA ◽  
Osamu MATSUMOTO ◽  
Yoshio MATSUMOTO ◽  
Tsukasa OGASAWARA

Robotica ◽  
2005 ◽  
Vol 23 (6) ◽  
pp. 681-688 ◽  
Author(s):  
Makoto Kern ◽  
Peng-Yung Woo

Fuzzy logic has features that are particular attractive in light of the problems posed by autonomous robot navigation. Fuzzy logic allows us to model different types of uncertainty and imprecision. In this paper, the implementation of a hexapod mobile robot with a fuzzy controller navigating in unknown environments is presented. The robot, MKIII, interprets input sensor data through the comparison of values in its fuzzy rule base and moves accordingly to avoid obstacles. Results of trial run experiments are presented.


Author(s):  
Vinod Kapse ◽  
Bhavana Jharia ◽  
S. S. Thakur ◽  
C. P. Gupta

The analog fuzzy intelligent controllers for autonomous mobile robot to avoid static and dynamic obstacles in its local environment are presented. The controller designed for the robot is reconfigurable in nature in terms of number of rules in database i.e. flexibility for online rule change as per the frequency of obstacle in the local environment. The controller is proposed with adjustable membership function in terms of shape and degree of overlapping with dynamic rule base. New accurate MAX and MIN circuits are introduced. The controller is simulated using Tanner® tool. The two-input single-output fuzzy controller with 25 rules is implemented in 0.25µm CMOS technology. The maximum delay was found to be 9.915ns for the processing of 25 rules and the value of FLIPS was found to be 100.85 MFLIPS.


1996 ◽  
Vol 7 (1) ◽  
pp. 77-84 ◽  
Author(s):  
Y. S. Tarng ◽  
C. Y. Lin ◽  
C. Y. Nian

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