Brendan Hertel

2 accepted papers

2022

Robot Learning from Demonstration Using Elastic Maps

Brendan Hertel, Matthew Pelland, S. Reza Ahmadzadeh

IROS 2022poster

Learning from Demonstration (LfD) is a popular method of reproducing and generalizing robot skills from human-provided demonstrations. In this paper, we propose a novel optimization-based LfD method that encodes demon-strations as elastic maps. An elastic map is a graph of nodes connected through a…

Cited by 8 Source ↗code ↗Scholar ↗

2021

Learning from Successful and Failed Demonstrations via Optimization

Brendan Hertel, S. Reza Ahmadzadeh

IROS 2021poster

Learning from Demonstration (LfD) is a popular approach that allows humans to teach robots new skills by showing the correct way(s) of performing the desired skill. Human-provided demonstrations, however, are not always optimal and the teacher usually addresses this issue by discarding or replacing…

Cited by 9 Source ↗code ↗Scholar ↗