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Title: Grasping Fragile Objects Using A Stress-Minimization Metric
We present a new method to generate optimal grasps for brittle and fragile objects using a novel stressminimization (SM) metric. Our approach is designed for objects that are composed of homogeneous isotopic materials. Our SM metric measures the maximal resistible external wrenches that would not result in fractures in the target objects. In this paper, we propose methods to compute our new metric. We also use our SM metric to design optimal grasp planning algorithms. Finally, we compare the performance of our metric and conventional grasp metrics, including Q1, Q∞, QG11, QMSV , QV EW . Our experiments show that our SM metric takes into account the material characteristics and object shapes to indicate the fragile regions, where prior methods may not work well. We also show that the computational cost of our SM metric is on par with prior methods. Finally, we show that grasp planners guided by our metric can lower the probability of breaking target objects.  more » « less
Award ID(s):
1910486
NSF-PAR ID:
10190830
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
International Conference on Robotics and Automation (ICRA 2020)
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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