Comparing Mobile Robot Navigation by combined ACO and ICA with Fuzzy Logic in unknown environments

Path planning for robot’s movement is an important branch of research in robotics science. In this paper, ACO algorithm and ICA are combined with fuzzy logic for route moving robot in unknown environments with various complexities. This new approach for solving mobile robot navigation in dynamic environments, based on the ICA algorithm is proposed. In this study, according to the proposed evaluation function, the found path is smoother and cleaner than previous studies done using other algorithms. Decision-making is influenced by the distances between the origin and destination points and the angle variance to the nearest obstacles. Ideal paths are selected by the fuzzy logic. The proposed ICA will optimize the fuzzy rules’ parameters that have been used to On-line path planning in dynamic environments. The performance of both combined algorithms in the execution speed and the number of occurrences for obtaining the optimal path in various unknown environments have been evaluated using MATLAB simulation methods. Obtained result from comparing the performance of these two algorithms developed optimization algorithms for mobile robots path planning

Keywords:

ACO algorithm , ICA algorithm , fuzzy logic , The dynamic environments , Mobile robots