The human hand's complex kinematics allow for simultaneous grasping and
manipulation of multiple objects, essential for tasks like object transfer and
in-hand manipulation. Despite its importance, robotic multi-object grasping
remains underexplored and presents challenges in kinematics, dynamics, and
object configurations. This paper introduces MultiGrasp, a two-stage method for
multi-object grasping on a tabletop with a multi-finger dexterous hand. It
involves (i) generating pre-grasp proposals and (ii) executing the grasp and
lifting the objects. Experimental results primarily focus on dual-object
grasping and report a 44.13% success rate, showcasing adaptability to unseen
object configurations and imprecise grasps. The framework also demonstrates the
capability to grasp more than two objects, albeit at a reduced inference speed.

该论文介绍了 MultiGrasp，一种用于多指灵巧机械手在桌面上进行多物体抓取的两阶段方法，包括生成抓前提案和执行抓取举起物体。实验结果主要集中在双物体抓取，并报告了 44.13% 的成功率，展示了对未见物体配置和不精确抓取的适应性。该框架还展示了抓取超过两个物体的能力，但推理速度较慢。