ICRA 2012 Paper Abstract


Paper WeB08.6

Kroemer, Oliver (Max-Planck Institute for Biological Cybernetics), Ugur, Emre (National Institute of Information and Comunications Technology (), Oztop, Erhan (Ozyegin University), Peters, Jan (Technische Universitšt Darmstadt)

A Kernel-Based Approach to Direct Action Perception

Scheduled for presentation during the Regular Session "Parts Handling and Manipulation" (WeB08), Wednesday, May 16, 2012, 11:45−12:00, Meeting Room 8 (Wacipi)

2012 IEEE International Conference on Robotics and Automation, May 14-18, 2012, RiverCentre, Saint Paul, Minnesota, USA

This information is tentative and subject to change. Compiled on June 20, 2018

Keywords Learning and Adaptive Systems, Dexterous Manipulation


The direct perception of actions allows a robot to predict the afforded actions of observed objects. In this paper, we present a non-parametric approach to representing the affordance-bearing subparts of objects. This representation forms the basis of a kernel function for computing the similarity between different subparts. Using this kernel function, together with motor primitive actions, the robot can learn the required mappings to perform direct action perception. The proposed approach was successfully implemented on a real robot, which could then quickly learn to generalize grasping and pouring actions to novel objects.



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