Robotic Mushroom Harvesting by Employing Probabilistic Road Map and Inverse Kinematics

Abstract

A collision-free path to a destination position in a random farm is determined using a probabilistic roadmap (PRM) that can manage static and dynamic obstacles. The position of ripening mushrooms is a result of picture processing. A mushroom harvesting robot is explored that uses inverse kinematics (IK) at the target position to compute the state of a robotic hand for grasping a ripening mushroom and plucking it. The Denavit-Hartenberg approach was used to create a kinematic model of a two-finger dexterous hand with three degrees of freedom for mushroom picking. Unlike prior experiments in mushroom harvesting, mushrooms are not planted in a grid or design, but are randomly scattered. At any point throughout the harvesting process, no human interaction is necessary.