A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Learning Dextrous Manipulation Skills for Multifingered Robot Hands Using the Evolution Strategy
1998
Machine Learning
We present a method for autonomous learning of dextrous manipulation skills with multifingered robot hands. We use heuristics derived from observations made on human hands to reduce the degrees of freedom of the task and make learning tractable. Our approach consists of learning and storing a few basic manipulation primitives for a few prototypical objects and then using an associative memory to obtain the required parameters for new objects and/or manipulations. The parameter space of the
doi:10.1023/a:1007409228154
dblp:journals/ml/FuentesN98
fatcat:wlstcwcx2jgvdjed5gk3nkkbz4