@poster{6852,
  title = {Generalizing Demonstrated Actions in Manipulation Tasks},
  journal = {IROS 2010 Workshop on Grasp Planning and Task Learning by Imitation},
  abstract = {Programming-by-demonstration promises to significantly reduce the burden of coding robots to perform new tasks. However, service robots will be presented with a variety of different situations that were not specifically 
  demonstrated to it. In such cases, the robot must autonomously generalize its learned motions to these new situations. We propose a system that can generalize movements to new target locations and even new objects. The former is achieved by using a task-specific coordinate system together with dynamical systems motor primitives. Generalizing actions to new 
  objects is a more complex problem, which we solve by treating it as a 
  continuum-armed bandits problem. Using the bandits framework, we can 
  efficiently optimize the learned action for a specific object. The proposed method was implemented on a real robot and succesfully adapted the grasping action to three different objects. Although we focus on grasping as an example of a task, the proposed methods are much more widely applicable to robot manipulation tasks.},
  volume = {2010},
  pages = {1},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  month = oct,
  year = {2010},
  slug = {6852},
  author = {Kroemer, O. and Detry, R. and Piater, J. and Peters, J.},
  month_numeric = {10}
}