Motion planning of an autonomous mobile robot by integrating GAs and fuzzy logic control

Abstract

The aim of the paper is to determine optimal motion planning for an autonomous mobile robot (AMR) moving in an environment with obstacles. We propose two motion planning methods, one is the linear vertex decision mechanism (LVDM) and the other is the fuzzy logic decision mechanism (FLDM). Computer simulations are explored to compare the performance of these two mechanisms. Furthermore, we apply genetic algorithms (GAs) to the LVDM to select the optimal weighting factor and we also adopt GAs in the FLDM such that the best membership function and/or the number of fuzzy control rules can be obtained. Computer simulations of the evolved LVDM and FLDM with GAs are also provided. All the simulations demonstrate that the proposed schemes can indeed guide the AMR even if the environment is filled with obstacles.