Semantic labeling of 3D point clouds with object affordance for robot manipulation

@article{Kim2014SemanticLO,
  title={Semantic labeling of 3D point clouds with object affordance for robot manipulation},
  author={David Inkyu Kim and Gaurav S. Sukhatme},
  journal={2014 IEEE International Conference on Robotics and Automation (ICRA)},
  year={2014},
  pages={5578-5584}
}
When a robot is deployed it needs to understand the nature of its surroundings. In this paper, we address the problem of semantic labeling 3D point clouds by object affordance (e.g., `pushable', `liftable'). We propose a technique to extract geometric features from point cloud segments and build a classifier to predict associated object affordances. With the classifier, we have developed an algorithm to enhance object segmentation and reduce manipulation uncertainty by iterative clustering… CONTINUE READING

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