DocumentCode :
137914
Title :
Single muscle site sEMG interface for assistive grasping
Author :
Weisz, Jonathan ; Barszap, Alexander G. ; Joshi, Sanjay S. ; Allen, Peter K.
Author_Institution :
Dept. of Comput. Sci., Columbia Univ., New York, NY, USA
fYear :
2014
fDate :
14-18 Sept. 2014
Firstpage :
2172
Lastpage :
2178
Abstract :
We present a joint demonstration between the Robotics, Autonomous Systems, and Controls Laboratory (RASCAL) at UC Davis and the Columbia University Robotics Group, wherein a human-in-the-loop robotic grasping platform in the Columbia lab (New York, NY) is controlled to select and grasp an object by a C3-C4 spinal cord injury (SCI) subject in the UC Davis lab (Davis, CA) using a new single-signal, multi-degree-of-freedom surface electromyography (sEMG) human-robot interface. The grasping system breaks the grasping task into a multi-stage pipeline that can be navigated with only a few inputs. It integrates pre-planned grasps with on-line grasp planning capability and an object recognition and target selection system capable of handling multi-object scenes with moderate occlusion. Previous work performed in the RASCAL lab demonstrated that by continuously modulating the power in two individual bands in the frequency spectrum of a single sEMG signal, users were able to control a cursor in 2D for cursor to target tasks. Using this paradigm, four targets were presented in order for the subject to command the multi-stage grasping pipeline. We demonstrate that using this system, operators are able to grasp objects in a remote location using a robotic grasping platform.
Keywords :
control engineering computing; electromyography; handicapped aids; human-robot interaction; manipulators; object recognition; telerobotics; C3-C4 spinal cord injury subject; assistive grasping; cursor control; human-in-the-loop robotic grasping platform; multidegree-of-freedom sEMG human-robot interface; multidegree-of-freedom surface electromyography human-robot interface; multiobject scenes; multistage grasping pipeline; object grasping; object recognition system; on-line grasp planning capability; single muscle site sEMG interface; single sEMG signal frequency spectrum; target selection system; Ear; Electrodes; Grasping; Muscles; Pipelines; Planning; Robots;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS 2014), 2014 IEEE/RSJ International Conference on
Conference_Location :
Chicago, IL
Type :
conf
DOI :
10.1109/IROS.2014.6942855
Filename :
6942855
Link To Document :
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