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Tangled: Learning to untangle ropes with RGB-D perception
2013
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
In this paper, we address the problem of manipulating deformable objects such as ropes. Starting with an RGB-D view of a tangled rope, our goal is to infer its knot structure and then choose appropriate manipulation actions that result in the rope getting untangled. We design appropriate features and present an inference algorithm based on particle filters to infer the rope's structure. Our learning algorithm is based on max-margin learning. We then choose an appropriate manipulation action
doi:10.1109/iros.2013.6696448
dblp:conf/iros/LuiS13
fatcat:4rjc44zpozgbdguedlp3lf55n4