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Paper ThA105.1

Aleotti, Jacopo (University of Parma), Caselli, Stefano (University of Parma)

Part-Based Robot Grasp Planning from Human Demonstration

Scheduled for presentation during the Regular Sessions "Manipulation Planning I" (ThA105), Thursday, May 12, 2011, 08:20−08:35, Room 3G

2011 IEEE International Conference on Robotics and Automation, May 9-13, 2011, Shanghai International Conference Center, Shanghai, China

This information is tentative and subject to change. Compiled on May 23, 2019

Keywords Manipulation Planning, Learning and Adaptive Systems, Grasping

Abstract

In this work we introduce a novel approach for robot grasp planning. The proposed method combines the benefits of programming by human demonstration for teaching appropriate grasps with those of automatic 3D shape segmentation for object recognition and semantic modeling. The work is motivated by important studies on human manipulation suggesting that when an object is perceived for grasping it is first parsed in its constituent parts. Following these findings we present a manipulation planning system capable of grasping objects by their parts which learns new tasks from human demonstration. The central advantage over previous approaches is the use of a topological method for shape segmentation enabling both object retrieval and part-based grasp planning according to the affordances of an object. Manipulation tasks are demonstrated in a virtual reality environment using a data glove. After the learning phase, each task is planned and executed in a robot environment that is able to generalize to similar, but previously unknown, objects.

 

 

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