Dynamic path planning and decentralized FLC path following implementation for WMR based on visual servoing

This paper presents an implementation and practical results for dynamic path planning and robot navigation for a non-holonomic indoor wheeled mobile robot (WMR) based on visual servoing. The proposed algorithm is based on the visual information extracted from a single ceiled IP-camera in the overall its stages. The algorithm is divided into three stages; the first stage analyzes the working environment to plan a safe and optimal robot' path based on Multi-Stencils Fast Marching (MSFM) as a path-planning technique. Generally, the fast marching planning methods when used directly does not generate a safe path. Consequently, the robot can touch walls, corners, and obstacles. The proposed algorithm merges the image processing and MSFM to generate a safe and optimal shortest path. The second stage tracks the robot motion and estimates its position and orientation based on visual feature information. The third stage is the control loop algorithm, which is based on a proportional derivative Fuzzy Logic Controller (PD-like FLC) in a decentralized form, to keep up the robot on the desired path. Experimental results show the validity of the developed design to estimate the optimal path to avoiding moving obstacles and its ability to guide the robot to follow the desired path under variable conditions in real-time.