Abstract
Robotic grasping has been conceived as pivotal in achieving a broad spectrum of mechanical functionalities, including motion planning and perceptions via proprio- or exteroceptive sensory feedback control. In the last decade, these efforts have led to the development of artificial grippers that can provide multiple grasping modalities while handling various objects. Nonetheless, most of today’s grippers require a particular posture for a given set of functions and tasks with fixed scenarios, which results in concreating grasping pipelines for known and unknown objects. In this work, a double-fingered gripper is presented using a kirigami pattern. To optimize the posture of two kirigami-inspired fingers, SOFA (Simulation Open Framework Architecture) is employed, and we focus on how the posture of two fingers influences to forming of a set of contact points concerning the target object. Overall, the optimal posture of the kirigami-inspired two-fingered gripper is demonstrated.
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Nardin, A.B., Joe, S., Beccai, L. (2023). Optimization of Kirigami-Inspired Fingers Grasping Posture in Virtual Environments. In: Meder, F., Hunt, A., Margheri, L., Mura, A., Mazzolai, B. (eds) Biomimetic and Biohybrid Systems. Living Machines 2023. Lecture Notes in Computer Science(), vol 14158. Springer, Cham. https://doi.org/10.1007/978-3-031-39504-8_10
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