125 research outputs found
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Haptic Perception with a Robot Hand: Requirements and Realization
This paper first discusses briefly some of the recent ideas of perceptual psychology on the human haptic system particularly those of J.J. Gibson and Klatzky and Lederman. Following this introduction, we present some of the requirements of robotic haptic sensing and the results of experiments using a Utah/MIT dexterous robot hand to derive geometric object information using active sensing
Design of a Multimodal Fingertip Sensor for Dynamic Manipulation
We introduce a spherical fingertip sensor for dynamic manipulation. It is
based on barometric pressure and time-of-flight proximity sensors and is
low-latency, compact, and physically robust. The sensor uses a trained neural
network to estimate the contact location and three-axis contact forces based on
data from the pressure sensors, which are embedded within the sensor's sphere
of polyurethane rubber. The time-of-flight sensors face in three different
outward directions, and an integrated microcontroller samples each of the
individual sensors at up to 200 Hz. To quantify the effect of system latency on
dynamic manipulation performance, we develop and analyze a metric called the
collision impulse ratio and characterize the end-to-end latency of our new
sensor. We also present experimental demonstrations with the sensor, including
measuring contact transitions, performing coarse mapping, maintaining a contact
force with a moving object, and reacting to avoid collisions.Comment: 6 pages, 2 pages of references, supplementary video at
https://youtu.be/HGSdcW_aans. Submitted to ICRA 202
The role of morphology of the thumb in anthropomorphic grasping : a review
The unique musculoskeletal structure of the human hand brings in wider dexterous capabilities to grasp and manipulate a repertoire of objects than the non-human primates. It has been widely accepted that the orientation and the position of the thumb plays an important role in this characteristic behavior. There have been numerous attempts to develop anthropomorphic robotic hands with varying levels of success. Nevertheless, manipulation ability in those hands is to be ameliorated even though they can grasp objects successfully. An appropriate model of the thumb is important to manipulate the objects against the fingers and to maintain the stability. Modeling these complex interactions about the mechanical axes of the joints and how to incorporate these joints in robotic thumbs is a challenging task. This article presents a review of the biomechanics of the human thumb and the robotic thumb designs to identify opportunities for future anthropomorphic robotic hands
On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation
Biological and robotic grasp and manipulation are undeniably similar at the
level of mechanical task performance. However, their underlying fundamental
biological vs. engineering mechanisms are, by definition, dramatically
different and can even be antithetical. Even our approach to each is
diametrically opposite: inductive science for the study of biological systems
vs. engineering synthesis for the design and construction of robotic systems.
The past 20 years have seen several conceptual advances in both fields and the
quest to unify them. Chief among them is the reluctant recognition that their
underlying fundamental mechanisms may actually share limited common ground,
while exhibiting many fundamental differences. This recognition is particularly
liberating because it allows us to resolve and move beyond multiple paradoxes
and contradictions that arose from the initial reasonable assumption of a large
common ground. Here, we begin by introducing the perspective of neuromechanics,
which emphasizes that real-world behavior emerges from the intimate
interactions among the physical structure of the system, the mechanical
requirements of a task, the feasible neural control actions to produce it, and
the ability of the neuromuscular system to adapt through interactions with the
environment. This allows us to articulate a succinct overview of a few salient
conceptual paradoxes and contradictions regarding under-determined vs.
over-determined mechanics, under- vs. over-actuated control, prescribed vs.
emergent function, learning vs. implementation vs. adaptation, prescriptive vs.
descriptive synergies, and optimal vs. habitual performance. We conclude by
presenting open questions and suggesting directions for future research. We
hope this frank assessment of the state-of-the-art will encourage and guide
these communities to continue to interact and make progress in these important
areas
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Robot learning of everyday object manipulations via human demonstration
We deal with the problem of teaching a robot to manipulate everyday objects through human demonstration. We first design a task descriptor which encapsulates important elements of a task. The design originates from observations that manipulations involved in many everyday object tasks can be considered as a series of sequential rotations and translations, which we call manipulation primitives. We then propose a method that enables a robot to decompose a demonstrated task into sequential manipulation primitives and construct a task descriptor. We also show how to transfer a task descriptor learned from one object to similar objects. In the end, we argue that this framework is highly generic. Particularly, it can be used to construct a robot task database that serves as a manipulation knowledge base for a robot to succeed in manipulating everyday objects
On neuromechanical approaches for the study of biological and robotic grasp and manipulation
abstract: Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank and open-minded assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas at the interface of neuromechanics, neuroscience, rehabilitation and robotics.The electronic version of this article is the complete one and can be found online at: https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-017-0305-
Low power glove for hand functioning analysis in children with cerebral palsy
In this paper, a low-cost glove has been manufactured to monitor and analyse the hand motion for the children who suffer from the cerebral palsy. Cerebral palsy (CP) is a combination of continual disorders affect the movement’s evolution due to a non-gradual disturbance in developing fetal or infant cerebrum. An Arduino Nano microcontroller with flex and force sensors are attached to soft cloth glove to form the analysis glove. The data of this study is collected from children who have cerebral palsy, non-cerebral palsy, and children who are treating by physiotherapy and then compared with each other. The results show that the analysis glove helps the physiotherapist to assess the hand functioning problem such as difficulty in hand grip and inability to fully bend the hand figures in general and thumb figure in particular. These remarks can help physiotherapists to define the required program to improve these functions and indications
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