Mobile Robot Path Planning Based on Chaos Generated by Utilizing Logistic Map

This study investigated motion planning of a mobile robot by utilizing the phenomena generated from four numerical models. Using the trajectory generated from the numerical models because the method can be applied to multiple fields, we considered a mobile robot that can entirely cover a specific region. In some previously conducted conventional studies, chaotic trajectories were applied to generate from the following four numerical models: the Arnold equations model, a two-dimensional discrete-time model derived from the chaotic neuron model, the logistic map model, and a random walk model. For the logistic map model, we generated chaotic behavior by setting an appropriate parameter value, which was used to change the angle of a mobile robot. On the basis of the simulation results, we calculated the sample variances demonstrating the distribution of the positions of a mobile robot on an xy-plane. We evaluated the effectiveness of the trajectories to cover the whole region. In addition, we compared the computational speed of the generation of each trajectory. The results of the investigation illustrate that the logistic map model was highly effective regarding our purpose. To achieve two degrees of freedom motion in the future, we are going to implement each method using an autonomous mobile robot, which has two active and independent wheels, and one passive wheel.