NDLI: Evaluating human gaze patterns during grasping tasks: robot versus human hand

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Evaluating human gaze patterns during grasping tasks: robot versus human hand

Content Provider	ACM Digital Library
Author	Dixit, Saurabh Grimm, Cindy Ruiz, Javier Balasubramanian, Ravi Allani, Sai Krishna John, Brendan Carter, Jackson
Abstract	Perception and gaze are an integral part of determining where and how to grasp an object. In this study we analyze how gaze patterns differ when participants are asked to manipulate a robotic hand to perform a grasping task when compared with using their own. We have three findings. First, while gaze patterns for the object are similar in both conditions, participants spent substantially more time gazing at the robotic hand then their own, particularly the wrist and finger positions. Second, We provide evidence that for complex objects (eg, a toy airplane) participants essentially treated the object as a collection of sub-objects. Third, we performed a follow-up study that shows that choosing camera angles that clearly display the features participants spend time gazing at are more effective for determining the effectiveness of a grasp from images. Our findings are relevant both for automated algorithms (where visual cues are important for analyzing objects for potential grasps) and for designing tele-operation interfaces (how best to present the visual data to the remote operator).
Starting Page	45
Ending Page	52
Page Count	8
File Format	PDF
ISBN	9781450343831
DOI	10.1145/2931002.2931007
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-07-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Robot grasp Eye-gaze Camera control
Content Type	Text
Resource Type	Article

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