Ian M. Bullock

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This paper presents a dataset of human grasping behavior in unstructured environments. Wide-angle head-mounted camera video was recorded from two housekeepers and two machinists during their regular work activities, and the grasp types, objects, and tasks were analyzed and coded by study staff. The full dataset contains 27.7 hours of tagged video and(More)
In this paper, we present results from a study of prehensile human hand use during the daily work activities of four subjects: two housekeepers and two machinists. Subjects wore a head-mounted camera that recorded their hand usage during their daily work activities in their typical place of work. For each subject, 7.45 hours of video was analyzed, recording(More)
This work contributes to the development of a common framework for the discussion and analysis of dexterous manipulation across the human and robotic domains. An overview of previous work is first provided along with an analysis of the tradeoffs between arm and hand dexterity. A hand-centric and motion-centric manipulation classification is then presented(More)
This paper presents a taxonomy for detailed classification of human and anthropomorphic manipulation behavior. This hand-centric, motion-centric taxonomy differentiates tasks based on criteria such as object contact, prehension, and the nature of object motion relative to a hand frame. A sub-classification of the most dexterous categories, within-hand(More)
Robotic and prosthetic hand designers are challenged to replicate as much functionality of the human hand as possible, while minimizing cost and any unnecessary complexity. Selecting which aspects of human hand function to emulate can be difficult, especially when little data is available on unstructured human manipulation behavior. The present work(More)
The incredible complexity of the human hand makes accurate modeling difficult. When implementing a kinematic hand model, many simplifications are made, either to provide simpler analytical solutions, to ease implementation, or to speed up computation for real time applications. However, it is important to understand the trade-offs that certain(More)
Precision manipulation, in which an object held between the fingertips is translated and/or rotated with respect to the hand without sliding, is used frequently in everyday tasks such as writing, yet few studies have examined the experimental precision manipulation workspace of the human hand. This study evaluates the range of positions over which 19(More)
This paper is the second in a two-part series analyzing human grasping behavior during a wide range of unstructured tasks. It investigates the tasks performed during the daily work of two housekeepers and two machinists and correlates grasp type and object properties with the attributes of the tasks being performed. The task or activity is classified(More)
Designing robot hands for dexterous precision manipulation involves many complex tradeoffs in order to optimize hand performance. While many studies focus on overall hand kinematics, far fewer consider tradeoffs in the design of the robotic finger surfaces themselves. Our present work uses 3.8 total hours of precision manipulation from 19 participants to(More)
This paper is the first of a two-part series analyzing human grasping behavior during a wide range of unstructured tasks. The results help clarify overall characteristics of human hand to inform many domains, such as the design of robotic manipulators, targeting rehabilitation toward important hand functionality, and designing haptic devices for use by the(More)