Optimization of Robotic Mobile Agent Navigation

摘要

The traveling salesman problem (TSP) has many applications in economy, transport logic [1] etc. It also has a wide range of applicability in the mobile robot path planning optimization The paper presents research result of solving the path planning subproblem of the navigation of an intelligent autonomous mobile robotic agent. Collecting objects by a mobile robotic agent is the final problem that is intended to be solved. For the robotic mobile agent's path planning is used an unsupervised neural network that can find a closely optimal path between two points in the agent's working area. We have considered a modification of the criteria function of the winner neuron selection. Simulation results are discussed at the end of the paper. The next future development is the hardware implementation of the selforganizing map with real time functioning.