INTELLIGENT CONTROL-SYSTEM SIMULATION OF AN AGRICULTURAL ROBOT

An intelligent control system for an agricultural robot which performs in an uncertain and unstructured environment was modelled as distributed, autonomous computing modules that communicate through globally accessible blackboard structures. The control architecture was implemented for a robotic harvester of melons. A CAD workstation was used to plan, model, simulate and evaluate the robot and gripper motions using 3-D, real-time animation. The intelligent control structure was verified by simulating the dynamic data flow scenarios of melon harvesting. Control algorithms were evaluated on measured melon locations. Picking time was reduced by 49% by applying the traveling salesman algorithm to define the picking sequence. Picking speeds can be increased by a continuous mode of operation. However, this decreases harvest efficiency. Therefore, an algorithm was developed to attain 100% harvest efficiency by varying the vehicle's forward speed. By comparing different motion control algorithms through animated visual simulation, the best was selected and thereby the performance improved.