MODIFICATION OF NEURAL NETWORK SYSTEM OF TRAJECTORIES PLANNING: TECHNIQUES AND RESULTS
This article contains the possible ways and algorithms for the optimization of the planning system based on the Hopfield neural network. These methods allow to increase, taking into account ability of onboard control and information complexes, efficiency of the processes of optimal path calculating. Thus, using the new activation function reduces the calculating complexity of the activation process and minimizes the appearance of local maximums on the neural map. Another variant of acceleration of the planning system is to use new algorithms for the creation of neural maps that take into account the specificity of information systems and the presence of dynamic obstacles in the working area. The proposed approach allowed us to get smoother and more efficient path. All the proposed methods in the article have been tested on mathematical models and experimental mobile robots. The obtained data demonstrates the increasing efficiency of the planning system.