Abstract
This paper presents the development of an automated guided vehicle with omni-wheels for autonomous navigation under a robot operating system framework. Specifically, a laser rangefinder-constructed two-dimensional environment map is integrated with a three-dimensional point cloud map to achieve real-time robot positioning, using the oriented features from accelerated segment testing and a rotated binary robust independent elementary feature detector-simultaneous localization and mapping algorithm. In the path planning for autonomous navigation of the omnidirectional mobile robot, we applied the A* global path search algorithm, which uses a heuristic function to estimate the robot position difference and searches for the best direction. Moreover, we employed the time-elastic-band method for local path planning, which merges the time interval of two locations to realize time optimization for dynamic obstacle avoidance. The experimental results verified the effectiveness of the applied algorithms for the omni-wheeled mobile robot. Furthermore, the results showed a superior performance over the adaptive Monte Carlo localization for robot localization and dynamic window approach for local path planning.