Evaluation of mapping and path planning for non-holonomic mobile robot navigation in narrow pathway for agricultural application

Abstract

This paper evaluates mapping and path planning methods for mobile robot with non-holonomic constraint in the narrow pathways. Selection of sensors such as depth camera or LiDAR sensor is complex problem as it depends on applications, demand for cost, robustness and data processing. Along with sensor selection map generation is essential task for mobile robot navigation. This paper presents experimental evaluation of laser-based mapping algorithm i.e., Gmapping and vision based mapping i.e., RTAB-Map. The platform used for autonomous navigation is mobile robot with nonholonomic constraint. The path planning for mobile robot with non-holonomic constraint is more complex as not all arbitrary trajectories are kinematically feasible. The application of mobile robot navigation is to transfer agriculture products in greenhouse from one place to another. Generally, the pathways of greenhouse are narrow, which often results in the planner failing to generate a traversable trajectory if the mobile robot is restricted to forward movement, hence the switchback (forward and backward) path planning is essential to navigate in such environments. In the following discussion, we implement the Reeds-Shepp curve based path planning for mobile robot with a non-holonomic constraint to navigate in narrow pathways. Reeds-Shepp curve can generate various combinations of such switch-back trajectories and it remains unmatched in terms of computation efficiency and reliability compared to other curves. Effectiveness of the proposed path planning method is validated experimentally.