2019/11/21 by Cassie Meeker, Meeker, Cassie, Maximilian Haas-Heger +3 · 1 citation
Engineering · Medicine · #FOS: Computer and information sciences #Robot Manipulation and Learning #Robotics (cs.RO) #Stroke Rehabilitation and Recovery #Teleoperation and Haptic Systems
paper · pdf · doi:10.48550/arxiv.1911.09565
openalex publication_date 2019/11/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Teleoperation is a valuable tool for robotic manipulators in highly\nunstructured environments. However, finding an intuitive mapping between a\nhuman hand and a non-anthropomorphic robot hand can be difficult, due to the\nhands' dissimilar kinematics. In this paper, we seek to create a mapping\nbetween the human hand and a fully actuated, non-anthropomorphic robot hand\nthat is intuitive enough to enable effective real-time teleoperation, even for\nnovice users. To accomplish this, we propose a low-dimensional teleoperation\nsubspace which can be used as an intermediary for mapping between hand pose\nspaces. We present two different methods to define the teleoperation subspace:\nan empirical definition, which requires a person to define hand motions in an\nintuitive, hand-specific way, and an algorithmic definition, which is\nkinematically independent, and uses objects to define the subspace. We use each\nof these definitions to create a teleoperation mapping for different hands. One\nof the main contributions of this paper is the validation of both the empirical\nand algorithmic mappings with teleoperation experiments controlled by ten\nnovices and performed on two kinematically distinct hands. The experiments show\nthat the proposed subspace is relevant to teleoperation, intuitive enough to\nenable control by novices, and can generalize to non-anthropomorphic hands with\ndifferent kinematics.\n