Augmented Reality interface to verify Robot Learning. - Maximilian Diehl; Alexander Plopski; Hirokazu Kato 001; Karinne Ramirez-Amaro (RO-MAN, 2020)

Automated Generation of Robotic Planning Domains from Observations. - Maximilian Diehl; Chris Paxton 001; Karinne Ramirez-Amaro (IROS, 2021)

Work in Progress - Automated Generation of Robotic Planning Domains from Observations. - Maximilian Diehl; Karinne Ramirez-Amaro (CoRR, 2021)

Optimizing robot planning domains to reduce search time for long-horizon planning. - Maximilian Diehl; Chris Paxton 001; Karinne Ramirez-Amaro (CoRR, 2021)

Why Did I Fail? A Causal-Based Method to Find Explanations for Robot Failures. - Maximilian Diehl; Karinne Ramirez-Amaro (IEEE Robotics Autom. Lett., 2022)

The Importance of Human Factors for Trusted Human-Robot Collaborations. - Karinne Ramirez-Amaro; Ilaria Torre 002; Maximilian Diehl; Emmanuel Dean (HAI, 2023)

Guided Demonstrations Using Automated Excuse Generation. - Maximilian Diehl; Tathagata Chakraborti; Karinne Ramirez-Amaro (CoRR, 2023)

A causal-based approach to explain, predict and prevent failures in robotic tasks. - Maximilian Diehl; Karinne Ramirez-Amaro (Robotics Auton. Syst., 2023)

Learning Robot Skills From Demonstration for Multi-Agent Planning. - Maximilian Diehl; Isacco Zappa; Andrea Maria Zanchettin; Karinne Ramirez-Amaro (CASE, 2024)

Generating and Transferring Priors for Causal Bayesian Network Parameter Estimation in Robotic Tasks. - Maximilian Diehl; Karinne Ramirez-Amaro (IEEE Robotics Autom. Lett., 2024)

Enabling Robots to Identify Missing Steps in Robot Tasks for Guided Learning from Demonstration. - Maximilian Diehl; Tathagata Chakraborti; Karinne Ramirez-Amaro (SII, 2025)

Leveraging Symbolic Models in Reinforcement Learning for Multi-skill Chaining*. - Wenhao Lu; Maximilian Diehl; Jonas Sjöberg; Karinne Ramirez-Amaro (SII, 2025)