Autonomous navigation for mobile robot is one of the key problems in the domain of robotics, and several technologies, such as path planning and map building, are involved. With computational intelligence, computers can simulate human intelligence by mathematical method to deal with sensor information, and implement intelligent behaviors. This dissertation is aimed at the application of computational intelligence in mobile robot navigation, and it is an effective way to improve the intelligence level of mobile robot. In this paper, the research context of robot navigation is studied in details firstly. Secondly, a navigation system is designed and implemented on the self-developed mobile robot with a modified geometrical interval type-2 fuzzy logic system presented and both the DSm theory and PSO algorithm introduced to robotics domain. Thirdly, an algorithm for the generation of fuzzy classification rules is proposed on the base of the learning ability of PSO. Concretely:1. A new method for map building based on Dezert-Smarandache theory (DSm) which is a methodology for data fusion problems is presented to record situation information. Fuzzy logic is adopted to build ultrasonic sensor model, and different measures are combined with DSm combination rules. Simulation and practical experiments are carried out and it is proved that the method given here behaves a good performance.2. A PSO type-reduction method is proposed to modify geometric interval type-2 fuzzy logic system.In PSO type-reduction method, type-reduction is converted into an optimization problem, so the inference principle of geometric interval FLS operating on continuous domain is consistent with that of traditional interval type-2 FLS which work on discrete domain. The reactive behaviors of obstacle avoidance and wall following are implemented through the modified GIT-2FLS. 3. A path planning algorithm based on particle swarm algorithm is proposed for structure situation. The fitness function consists of path length and obstacle constrain which is computed with neural network. The validity of the algorithm is proved in computer simulation. 4. An hybrid architecture of navigation system is designed and implemented on the self-developed mobile robot operated in half-structure situation. The performance of the navigation system is tested in the experiments.5. A new kind of algorithm is proposed for fuzzy rules’ generating from fuzzy data set. The algorithm is carried out to solve the famous “Saturday Morning Problem”, and the result is compared with that from fuzzy decision tree induction method.
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