Abstract
This paper develops techniques and methodologies for global path planning and navigation of a Mecanum-wheeled omnidirectional mobile robot (MWOMR). The proposed navigation system is composed of three modules: odometry, nonsingular terminal sliding-mode (NTSM) dynamic motion controller, and global path planner, which have been implemented using the SoPC technology. The odometry is constructed by using a numerical method and a kinematic model of the robot, in order to keep track of the current position and orientation of the robot over short distances. A nonsingular terminal sliding-mode dynamic controller is well derived to achieve simultaneous point stabilization and trajectory tracking. A hybrid PSO (particle swarm optimization)-RGA (real-coded genetic algorithm) algorithm is proposed to find an optimal path between a starting and ending point in a given grid environment. Simulations and experimental results are conducted which have shown the feasibility and effectiveness of the proposed global path planning and navigation methods.
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