Grasp Multiple Objects with One Hand

• URL: http://arxiv.org/abs/2310.15599v2
• Date: Thu, 14 Mar 2024 09:53:05 GMT
• Title: Grasp Multiple Objects with One Hand
• Authors: Yuyang Li, Bo Liu, Yiran Geng, Puhao Li, Yaodong Yang, Yixin Zhu, Tengyu Liu, Siyuan Huang,
• Abstract summary: MultiGrasp is a novel two-stage approach for multi-object grasping using a dexterous multi-fingered robotic hand on a tabletop. Our experimental focus is primarily on dual-object grasping, achieving a success rate of 44.13%. The framework demonstrates the potential for grasping more than two objects at the cost of inference speed.
• Score: 44.18611368961791
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The intricate kinematics of the human hand enable simultaneous grasping and manipulation of multiple objects, essential for tasks such as object transfer and in-hand manipulation. Despite its significance, the domain of robotic multi-object grasping is relatively unexplored and presents notable challenges in kinematics, dynamics, and object configurations. This paper introduces MultiGrasp, a novel two-stage approach for multi-object grasping using a dexterous multi-fingered robotic hand on a tabletop. The process consists of (i) generating pre-grasp proposals and (ii) executing the grasp and lifting the objects. Our experimental focus is primarily on dual-object grasping, achieving a success rate of 44.13%, highlighting adaptability to new object configurations and tolerance for imprecise grasps. Additionally, the framework demonstrates the potential for grasping more than two objects at the cost of inference speed.

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