5 papers
Confidence-Based Skill Reproduction Through Perturbation Analysis
Brendan Hertel, S. Reza Ahmadzadeh
Several methods exist for teaching robots, with one of the most prominent being Learning from Demonstration (LfD). Many LfD representations can be formulated as constrained optimiz…
Robot Learning from Demonstration Using Elastic Maps
Brendan Hertel, Matthew Pelland, S. Reza Ahmadzadeh
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 optimizatio…
Methods for Combining and Representing Non-Contextual Autonomy Scores for Unmanned Aerial Systems
Brendan Hertel, Ryan Donald, Christian Dumas +1
Measuring an overall autonomy score for a robotic system requires the combination of a set of relevant aspects and features of the system that might be measured in different units,…
Similarity-Aware Skill Reproduction based on Multi-Representational Learning from Demonstration
Brendan Hertel, S. Reza Ahmadzadeh
Learning from Demonstration (LfD) algorithms enable humans to teach new skills to robots through demonstrations. The learned skills can be robustly reproduced from the identical or…
Learning from Successful and Failed Demonstrations via Optimization
Brendan Hertel, S. Reza Ahmadzadeh
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…