3 papers
cs.RO2022
A Causal-based Approach to Explain, Predict and Prevent Failures in Robotic Tasks
Maximilian Diehl, Karinne Ramirez-Amaro
Robots working in real environments need to adapt to unexpected changes to avoid failures. This is an open and complex challenge that requires robots to timely predict and identify…
cs.RO2021
Work in Progress -- Automated Generation of Robotic Planning Domains from Observations
Maximilian Diehl, Karinne Ramirez-Amaro
In this paper, we report the results of our latest work on the automated generation of planning operators from human demonstrations, and we present some of our future research idea…
cs.RO2021
Automated Generation of Robotic Planning Domains from Observations
Maximilian Diehl, Chris Paxton, Karinne Ramirez-Amaro
Automated planning enables robots to find plans to achieve complex, long-horizon tasks, given a planning domain. This planning domain consists of a list of actions, with their asso…