Learning of Grasp Selection based on Shape-Templates





The ability to grasp unknown objects still remains an unsolved problem in the robotics community. One of the challenges is to choose an appropriate grasp configu- ration, i.e., the 6D pose of the hand relative to the object and its finger configuration. In this paper, we introduce an algo- rithm that is based on the assumption that similarly shaped objects can be grasped in a similar way. It is able to synthe- size good grasp poses for unknown objects by finding the best matching object shape templates associated with previously demonstrated grasps. The grasp selection algorithm is able to improve over time by using the information of previous grasp attempts to adapt the ranking of the templates to new situa- tions. We tested our approach on two different platforms, the Willow Garage PR2 and the Barrett WAM robot, which have very different hand kinematics. Furthermore, we compared our algorithm with other grasp planners and demonstrated its superior performance. The results presented in this paper show that the algorithm is able to find good grasp configura- tions for a large set of unknown objects from a relatively small set of demonstrations, and does improve its performance over time.

Author(s): Alexander Herzog and Peter Pastor and Mrinal Kalakrishnan and Ludovic Righetti and Jeannette Bohg and Tamim Asfour and Stefan Schaal
Journal: Autonomous Robots
Volume: 36
Number (issue): 1-2
Pages: 51-65
Year: 2014
Month: January
Publisher: Springer US

Department(s): Autonomous Motion, Movement Generation and Control
Research Project(s): Autonomous Robotic Manipulation
Template-Based Learning of Model Free Grasping
Bibtex Type: Article (article)
Paper Type: Journal

DOI: 10.​1007/​s10514-013-9366-8
State: Published

Links: video
Attachments: pdf


  title = {Learning of Grasp Selection based on Shape-Templates},
  author = {Herzog, Alexander and Pastor, Peter and Kalakrishnan, Mrinal and Righetti, Ludovic and Bohg, Jeannette and Asfour, Tamim and Schaal, Stefan},
  journal = {Autonomous Robots},
  volume = {36},
  number = {1-2},
  pages = {51-65},
  publisher = {Springer US},
  month = jan,
  year = {2014},
  month_numeric = {1}