Local path planning strategy: A practical implementation for versatile distance

In this paper we present a local path planning for autonomous robot navigation using spatial clustering based object detection. Autonomous navigation systems must be able to recognize objects in order to perform a collision free motion. First, obstacle detection strategy was proposed by using the Density-based spatial clustering of applications with noise (DBSCAN) method through a dynamic density-reachable implementation. Second, in order to determine an optimal path for collision avoidance a distance clustering analysis it was implemented. Then, the system follows the optimal path until a collision is detected or new path should be detected due to environmental uncertainty. Finally, to control the mobile robot, a fuzzy logic controller was implemented. These specific methods of measurement were chosen to prove their effectiveness.