Abstract
Selective harvesting for seasonal fruits like apples requires intensive manual labour in a short period; however, due to the delicate property of the fruits, it cannot be performed with an existing commercial machine, which urged to be replaced by robots. The goal of this study is to introduce a framework for motion and hierarchical task planning which allows the manipulator to pick apples in the orchard. The hierarchical task planning assures that the manipulator performs the harvesting task in the higher control level in corporation with other components: sensors system, mobile platform while dealing with the complicated and uncertain environment. The motion planning provides the abilities to the manipulator: to avoid the obstacles, to reach the targets, and to perform the detaching movement elaborated from a limited number of predefined strategies. This motion and task planning framework has been successfully evaluated in simulation, and the real-time tests show that the harvesting task is accomplished with assured communication between sensing, planning and executing.
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