58 citations · 134 across the 15 of their papers we have counts for
6 papers · 1 filter
Online Action Recognition
Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras +1
Recognition in planning seeks to find agent intentions, goals or activities given a set of observations and a knowledge library (e.g. goal states, plans or domain theories). In thi…
Task-Adaptive Robot Learning from Demonstration with Gaussian Process Models under Replication
Miguel Arduengo, Adrià Colomé, Júlia Borràs +2
Learning from Demonstration (LfD) is a paradigm that allows robots to learn complex manipulation tasks that can not be easily scripted, but can be demonstrated by a human teacher.…
Encoding cloth manipulations using a graph of states and transitions
Júlia Borràs, Guillem Alenyà, Carme Torras
Cloth manipulation is very relevant for domestic robotic tasks, but it presents many challenges due to the complexity of representing, recognizing and predicting the behaviour of c…
Leveraging Multiple Environments for Learning and Decision Making: a Dismantling Use Case
Alejandro Suárez-Hernández, Thierry Gaugry, Javier Segovia-Aguas +4
Learning is usually performed by observing real robot executions. Physics-based simulators are a good alternative for providing highly valuable information while avoiding costly an…
Gaussian-Process-based Robot Learning from Demonstration
Miguel Arduengo, Adrià Colomé, Joan Lobo-Prat +2
Endowed with higher levels of autonomy, robots are required to perform increasingly complex manipulation tasks. Learning from demonstration is arising as a promising paradigm for t…
STRIPS Action Discovery
Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras +1
The problem of specifying high-level knowledge bases for planning becomes a hard task in realistic environments. This knowledge is usually handcrafted and is hard to keep updated,…