@inproceedings{SmaDevGro1995, Author = {Smagt, Patrick van der and Dev, Anuj and Groen, Frans}, Title = {A visually guided robot and a neural network join to grasp slanted objects}, Year = {1995}, Pages = {144-150}, Month = {Sep.}, Editor = {B. Kappen and S. Gielen}, Publisher = {Foundation for Neural Networks, Nijmegen}, Address = {Nijmegen, Netherlands}, Booktitle = {Proceedings of the 3rd SNN Symposium on Neural Networks}, Keywords = {brml}, Abstract = {In this paper we introduce a method for model-free monocular visual guidance of a robot arm. The robot arm, with a single camera in its end-effector, should be positioned above a target, with a changing pan and tilt, which is placed against a textured background. It is shown that a trajectory can be planned in visual space by using components of the optic flow, and this trajectory can be translated to joint torques by a self-learning neural network. No model of the robot, camera, or environment is used. The method reaches a high grasping accuracy after only a few trials.} } @COMMENT{Bibtex file generated on 2018-10-9 with typo3 si_bibtex plugin. Data from https://brml.org/people/smagt/ }