Inter-Row Tree Detection and Tracking Schemes For Structural Plantation Area

In this work, an inter-row tree detection and tracking techniques based on Simultaneous Localization and Mapping (SLAM) method is developed specifically for a well-structures agricultural field where the trees are planted uniformly with certain distance that leaves it with a number of inter-row spaces. The existing rows has created opportunities for an autonomous vehicle to navigate in between the trees to perform the plantation activities such as scouting, monitoring, rowing, pesticide spraying and others. A new approach to detect the landmarks and navigate in the farm based on the lightweight sensors and less computation effort is proposed. In this method, the tree detection and diameter estimation techniques implement the modified tree-triangle diameter technique by using innovative technique based on infrared sensors. Then, in substituting the GPS signal problems during the navigation and localization problems, a curve-based navigation approach is formulated. The path is planned based on the third-polynomial Bezier curve by projecting series of waypoints to create a solid path from one point to another. Then, the trajectory plan is derived for the autonomous vehicle to follow these waypoints during the navigation. At the same time, the mapping technique implements the memory utilization method in order to ease the localization process as well as landmarks mapping in the visual map which is oriented in two-dimensional coordinate format. All of these functions are created, formulated and tested thoroughly in the embedded microcontroller development board platform by using dsPIC30F6014A chip on the omnidirectional vehicle platform.