Learning task constraints for robot grasping using graphical models

@article{Song2010LearningTC,
  title={Learning task constraints for robot grasping using graphical models},
  author={Dan Song and Kai Huebner and Ville Kyrki and Danica Kragic},
  journal={2010 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2010},
  pages={1579-1585}
}
This paper studies the learning of task constraints that allow grasp generation in a goal-directed manner. We show how an object representation and a grasp generated on it can be integrated with the task requirements. The scientific problems tackled are (i) identification and modeling of such task constraints, and (ii) integration between a semantically expressed goal of a task and quantitative constraint functions defined in the continuous object-action domains. We first define constraint… CONTINUE READING
Highly Cited
This paper has 74 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.
51 Citations
21 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 51 extracted citations

74 Citations

01020'11'13'15'17
Citations per Year
Semantic Scholar estimates that this publication has 74 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 21 references

Similar Papers

Loading similar papers…