Autonomous Navigation Using Robust SLAM and Genetic Algorithm
S. Ortiz-Santos, Wen Yu, Xiaoou Li · 2021
Autonomous navigation in unknown environment is a big challenge. It needs both good map and effective path planning algorithm for the unknown environment. In this paper, we use sliding mode method to improve the SLAM (simultaneous localization and mapping) with bounded uncertainties. Then we propose a novel path planning method based on the novel SLAM, which uses the genetic algorithm. This novel method takes the advantages of the robustness of the sliding mode method and the good convergence ability of the genetic algorithm. Comparisons with others popular methods are made to show the advantages of the proposed method.