Maximilian Diehl

Doctoral Student at Mechatronics

Maximilian Diehl is a PhD student in the Mechatronic research group. He works at the intersection of robotics and artificial intelligence. His main research interests are task planning and learning, learning from demonstration, and human-robot collaboration.

Source: chalmers.se
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Showing 10 publications

2024

Generating and Transferring Priors for Causal Bayesian Network Parameter Estimation in Robotic Tasks*

Maximilian Diehl, Karinne Ramirez-Amaro
IEEE Robotics and Automation Letters. Vol. 9 (2), p. 1011 -1018
Journal article
2024

Learning Robot Skills From Demonstration for Multi-Agent Planning

Maximilian Diehl, Isacco Zappa, Andrea Maria Zanchettin et al
IEEE International Conference on Automation Science and Engineering, p. 2348-2355
Paper in proceeding
2023

A causal-based approach to explain, predict and prevent failures in robotic tasks

Maximilian Diehl, Karinne Ramirez-Amaro
Robotics and Autonomous Systems. Vol. 162
Journal article
2023

The Importance of Human Factors for Trusted Human-Robot Collaborations

Karinne Ramirez-Amaro, Ilaria Torre, Maximilian Diehl et al
ACM International Conference Proceeding Series, p. 502-503
Paper in proceeding
2022

Why Did I Fail? a Causal-Based Method to Find Explanations for Robot Failures

Maximilian Diehl, Karinne Ramirez-Amaro
IEEE Robotics and Automation Letters. Vol. 7 (4), p. 8925-8932
Journal article
2021

Work in Progress - Automated Generation of Robotic Planning Domains from Observations

Maximilian Diehl, Karinne Ramirez-Amaro
18th International Conference on Ubiquitous Robots (UR), Organised session: 'Robots in the household: A review of task knowledge acquisition, planning, and execution'
Other conference contribution
2021

Optimizing robot planning domains to reduce search time for long-horizon planning

Maximilian Diehl, Chris Paxton, Karinne Ramirez-Amaro
Other conference contribution
2021

Automated Generation of Robotic Planning Domains from Observations

Maximilian Diehl, Chris Paxton, Karinne Ramirez-Amaro
IEEE International Conference on Intelligent Robots and Systems, p. 6732-6738
Paper in proceeding
2020

Augmented Reality interface to verify Robot Learning

Maximilian Diehl, Alexander Plopski, Hirokazu Kato et al
29th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2020, p. 378-383
Paper in proceeding

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Showing 1 research projects

2020–2025

Learning & Understanding Human-Centered Robotic Manipulation Strategies

Karinne Ramirez-Amaro Mechatronics
Yiannis Karayiannidis Mechatronics
Maximilian Diehl Mechatronics
Jonas Sjöberg Mechatronics
Chalmers AI Research Centre (CHAIR)

5 publications exist
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