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This paper introduces the iRobot-Harvard-Yale (iHY) Hand, an underactuated hand driven by 5 actuators that is capable of performing a wide range of grasping and in-hand repositioning tasks. This hand was designed to address the need for a durable, inexpensive, moderately dexterous hand suitable for use on mobile robots. The primary focus of this paper will(More)
Limitations in modern sensing technologies result in large errors in sensed target object geometry and location in unstructured environments. As a result, positioning a robotic end-effector includes inherent error that will often lead to unsuccessful grasps. In previous work, we demonstrated that optimized configuration, compliance, viscosity, and(More)
The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. Abstract—This paper presents a new approach to the construction of tactile array sensors based on barometric pressure sensor chips and standard printed circuit boards. The chips include tightly integrated instrumentation amplifiers,(More)
— To determine object geometry in unstructured environments, sensors must be mechanically robust, must exert only low forces on objects during exploration, and must be able to scan large regions efficiently without risk of damaging objects or sensors. Joint-angle sensors on compliant joints provide an appealing option for this task. An algorithmic framework(More)
— Grasping and manipulation in unstructured environments must handle a wide range of object properties and significant sensing errors. Underactuation and compliance have been shown to be an effective way to improve grasping performance under such uncertainty, but the degree of compliance plays an important role in both gently adapting to sensing errors and(More)
This paper examined how humans alter reach-to-grasp behavior to compensate for environmentally-induced object orientation uncertainty. We used a novel motion tracking framework to capture hand-object interactions, as well as a custom cylindrical object to detect contacts. Subjects were instructed to reach, grasp, and lift the object with or without vision.(More)
While polymeric fabrication processes, including recent advances in additive manufacturing, have revolutionized manufacturing, little work has been done on effective sensing elements compatible with and embedded within polymeric structures. In this paper, we describe the development and evaluation of two important sensing modalities for embedding in(More)
This paper presents the implementation of a robust grasp mapping between a 3-finger haptic device (master) and a robotic hand (slave). Mapping is based on a grasp equivalence defined considering the manipulation capabilities of the master and slave devices. The metrics that translate the human hand gesture to the robotic hand workspace are obtained through(More)
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