A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is
Humans perform tasks such as bowl mixing bi-manually, but programming them on a robot can be challenging specially in tasks that require force control or on-line stiffness modulation. In this paper we first propose a user-friendly setup for demonstrating bi-manual tasks, while collecting complementary information on motion and forces sensed on a robotic arm, as well as the human hand configuration and grasp information. Secondly for learning the task we propose a method for extracting taskdoi:10.1145/2559636.2559844 dblp:conf/hri/PaisB14 fatcat:7qnwip4ddrcvvmt4f7akoh7e2y