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Title: Tri-modal thin-film flexible electronic skin to augment robotic grasping
Robotic grasping is successful when a robot can sense and grasp an object without letting it slip. Beyond industrial robotic tasks, there are two main robotic grasping methods. The first is planning-based grasping where the object geometry is known beforehand and stable grasps are calculated using algorithms [1]. The second uses tactile feedback. Currently, there are capacitive sensors placed beneath stiff pads on the front of robotic fingers [2]. With post-execution grasp adjustment procedures to estimate grasp stability, a support vector machine classifier can distinguish stable and unstable grasps. The accuracy across the classes of tested objects is 81% [1]. We are proposing to improve the classifier's accuracy by wrapping flexible sensors around the robotic finger to gain information from the edges and sides of the finger.
Authors:
; ;
Award ID(s):
1734557
Publication Date:
NSF-PAR ID:
10066934
Journal Name:
MEMS 2018
Page Range or eLocation-ID:
886 to 888
Sponsoring Org:
National Science Foundation
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