DocumentCode :
2641542
Title :
Fuzzy Critic for intelligent planning by genetic algorithm
Author :
Shibata, Takanori ; Fukuda, Toshio ; Tanie, Kazuo
Author_Institution :
Mech. Eng. Lab., Tsukuba, Japan
fYear :
1993
fDate :
27-29 Sep 1993
Firstpage :
78
Lastpage :
85
Abstract :
A new strategy for motion planning is proposed. The strategy applies a genetic algorithm (GA) to optimize the motion planning. To evaluate the planned motion, the strategy also applies fuzzy logic to a fitness function. The fitness function is referred to as Fuzzy Critic. The Fuzzy Critic evaluates plans as populations in the GA with respect to multiple factors. Depending on the goals of the tasks, human operators can easily determine inference rules in the Fuzzy Critic because of the fuzzy logic. The strategy determines a path for a mobile robot which moves from a starting point to a goal point, while avoiding obstacles in a work space and picking up loads on the way. Simulation illustrates the effectiveness of the proposed strategy
Keywords :
fuzzy control; fuzzy logic; genetic algorithms; inference mechanisms; intelligent control; mobile robots; path planning; position control; Fuzzy Critic; fitness function; fuzzy logic; genetic algorithm; inference rules; intelligent planning; mobile robot; motion planning; obstacle avoidance; simulation; Fuzzy logic; Genetic algorithms; Humans; Intelligent robots; Mobile robots; Motion planning; Neural networks; Orbital robotics; Robot kinematics; Strategic planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Emerging Technologies and Factory Automation, 1993. Design and Operations of Intelligent Factories. Workshop Proceedings., IEEE 2nd International Workshop on
Conference_Location :
Palm Cove-Cairns, Qld.
Print_ISBN :
0-7803-0985-5
Type :
conf
DOI :
10.1109/ETFA.1993.396426
Filename :
396426
Link To Document :
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