A novel fuzzy three-dimensional grid navigation method for mobile robots

The objective of the autonomous navigation aims to achieve the self-motion control for a robot with the environmental feedbacks and becomes popular recently. Problems of complex modeling, large amount of calculation, and lacking of environmental information always exist in autonomous navigation methods. This article proposes a self-navigation method with a fuzzy three-dimensional grid depicted by dual two-dimensional grid maps. Meanwhile, a synthetic preprocess is presented to perform localization through switching among the weighted three-point localization method, the two-point localization method, and the weighted average localization method. For reducing the amount of calculation, an improved fuzzy three-dimensional grid mapping method where the three-dimensional map is described by dual two-dimensional grid maps, the identifier map, and the height map is designed. Especially, the static and dynamic information within the map are divided and updated fuzzily. The global path planning is performed with the static information, and the real-time obstacle avoidance is conducted with the dynamic information. The results of simulations and experiments demonstrate that the proposed method has better properties in efficiency of navigation and lower amount of calculation than the competing methods.