Mobile robot navigation algorithm using a vector-based topological map and virtual Jacobian

Abstract

In this paper, a vector-based topological map is to be built consisting of available directions (moving directions) and the distances between nodes. This map represents the whole environment as a skeleton, using nodes similar to vectors independent of geometrical information of obstacles. To build a vector-based topological map, the following are developed: (a) acquisition of reliable range values using local minimum values, (b) fuzzy inference system (FIS) for extracting available directions, and (c) collision avoidance using virtual Jacobians. First, only local minimum values are used among the range of sensor values in order to decrease the effect of specular reflection and calculate available directions using the FIS. Specially, the number of consequent membership functions is determined as the number of obstacle orientations around a mobile robot, enabling the mobile robot to find available directions independently of the geometrical information of obstacles. Finally, to avoid collisions, a virtual Jacobian method is used because a vector-based topological map does not include the geometrical information about obstacles. The proposed algorithms have been verified in the simulation and implemented on a robot in the real environment.

Simultaneous localization and mapping navigation of unmanned ground vehicle based on second-order smooth variable structure filter with improved technique to combat fading for advanced wireless communications

“…In our work, we used the Split and Merge method of line segment extraction using laser data which is largely used for extraction line based–feature process. 37–39…”