The Robotic Mushroom Harvesting by Employing Probabilistic Road Map and Inverse Kinematics
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Abstract
A collision-free path to a destination position in a random farm is determined using a probabilistic roadmap 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 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.