Learning the tactile signatures of prototypical object parts for robust part-based grasping of novel objects
2015 (English)In: Proceedings - IEEE International Conference on Robotics and Automation, IEEE conference proceedings, 2015, no June, 4927-4932 p.Conference paper (Refereed)
We present a robotic agent that learns to derive object grasp stability from touch. The main contribution of our work is the use of a characterization of the shape of the part of the object that is enclosed by the gripper to condition the tactile-based stability model. As a result, the agent is able to express that a specific tactile signature may for instance indicate stability when grasping a cylinder, while cuing instability when grasping a box. We proceed by (1) discretizing the space of graspable object parts into a small set of prototypical shapes, via a data-driven clustering process, and (2) learning a touch-based stability classifier for each prototype. Classification is conducted through kernel logistic regression, applied to a low-dimensional approximation of the tactile data read from the robot's hand. We present an experiment that demonstrates the applicability of the method, yielding a success rate of 89%. Our experiment also shows that the distribution of tactile data differs substantially between grasps collected with different prototypes, supporting the use of shape cues in touch-based stability estimators.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2015. no June, 4927-4932 p.
Clustering algorithms, Stability, Clustering process, Data driven, Kernel logistic regression, Low-dimensional approximation, Object grasps, Part based, Robotic agents, Stability models, Robotics
Electrical Engineering, Electronic Engineering, Information Engineering
IdentifiersURN: urn:nbn:se:kth:diva-176113DOI: 10.1109/ICRA.2015.7139883ISI: 000370974904126ScopusID: 2-s2.0-84938239973OAI: oai:DiVA.org:kth-176113DiVA: diva2:874754
2015 IEEE International Conference on Robotics and Automation, ICRA 2015, 26 May - 30 May 2015
QC 20151127. QC 201604112015-11-272015-11-022016-04-11Bibliographically approved