@INPROCEEDINGS{526258,
title={A sensor-based approach for motion in contact in task planning},
author={Cervera, E. and del Pobil, A.P. and Marta, E. and Serna, M.A.},
booktitle={Intelligent Robots and Systems 95. 'Human Robot Interaction and Cooperative Robots', Proceedings. 1995 IEEE/RSJ International Conference on},
year={1995},
month={Aug},
volume={2},
number={},
pages={468-473 vol.2},
abstract={A novel approach based on the use of force sensors for motion in contact with uncertainty in task planning is presented. A neural network monitors the force signals measured by a sensor mounted in the robot wrist. This network is able to learn without need of a teacher the different contact states of the system. The method is intended to work properly in complex real-world situations, for which a geometric analytical model may not be feasible, or too difficult. In this paper the authors study the two-dimensional peg-in-hole problem and a real example of a complex insertion task in a flexible manufacturing system },
keywords={ flexible manufacturing systems, monitoring, path planning, self-organising feature maps, unsupervised learning complex insertion task, flexible manufacturing system, force sensors, neural network, robot wrist, sensor-based approach, task planning, two-dimensional peg-in-hole problem},
doi={10.1109/IROS.1995.526258},
ISSN={}, }