Title :
Solving robot motion planning problem using Hopfield neural network in a fuzzified environment
Author :
Sadati, Nasser ; Taheri, Javid
Author_Institution :
Dept. of Electr. Eng., Sharif Univ. of Technol., Tehran, Iran
fDate :
6/24/1905 12:00:00 AM
Abstract :
In this paper, a new approach based on artificial neural networks to solve the robot motion planning problem is presented. For this purpose, a Hopfield neural network is used in a certain constraint satisfaction problem of the robot motion planning in conjunction with fuzzy modeling of the real robot´s environment so that the energy of a state can be interpreted as the extent to which a hypothesis fit the underlying neural formulation model. Thus, low energy values indicate a good level of constraint satisfaction of the problem. Finally, since the obtained answer by the Hopfield neural network is not optimal, some algorithms are designed to optimize and generate the final answer
Keywords :
Hopfield neural nets; constraint theory; fuzzy set theory; mobile robots; path planning; Hopfield neural network; constraint satisfaction; constraint satisfaction problem; fuzzified environment; robot motion planning problem; Artificial neural networks; Computational geometry; Fuzzy neural networks; Hopfield neural networks; Intelligent networks; Motion planning; Neural networks; Optimization methods; Orbital robotics; Robot motion;
Conference_Titel :
Fuzzy Systems, 2002. FUZZ-IEEE'02. Proceedings of the 2002 IEEE International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7280-8
DOI :
10.1109/FUZZ.2002.1006665