Fuzzy artmap neural networks (FAMNN) based navigation for intelligent autonomous vehicles (IAV) in partially structured environments

摘要

The use of Hybrid Intelligent Systems (HIS) is necessary to bring the behavior of Intelligent Autonomous Vehicles (IAV) near the human one in recognition, learning, decision-making, and action. First, the necessity of HIS and some navigation approaches based on Fuzzy ArtMap Neural Networks (FAMNN) are discussed. Second, a FAMNN based navigation approach, is suggested. Indeed, this approach must provide vehicles with capability, after supervised fast stable learning: Simplified Fuzzy ARTMAP (SFAM), to recognize both target location and obstacle avoidance situatiious using FAMNN_1 and FAMM_2, respectively. Afterwards, the decision-making and action consist of two association stages, carried out by reinforcement Trial and Error learning, and their coordination using NN_3. Finally, simulation results which display the ability of the FAMNN based approach providing IAV with capability to intelligently navigate in partially structured environments.