Research interests

My research is concerned with autonomous robots, with a particular far-fetched focus on robots that are one day supposed to support us in our everyday lives, for instance as household assistants. I am particularly interested in the following aspects of robotics:

• Robot introspection, fault detection and diagnosis: When I first joined the robotics field, I didn’t have robot faults on my radar, but, thanks to my eventual PhD advisor, I started working on different aspects of robot fault analysis quite early, so much that this has become my primary research passion. I believe that robots can only be useful in everyday applications if they are equipped with appropriate mechanisms for detecting their own failures and analysing those accordingly, potentially over a long time horizon - after all, we expect that any intelligent person can do this as well, so there is no reason to hold robots to a different standard if they are supposed to be integrated into our daily lives. My particular interest here is on execution failures, namely failures that a robot encounters while executing various skills, particularly in the context of learning-based skills.
• Cognitive robotics: I don’t know if we should necessarily aim to emulate human intelligence in robotics, particularly because our own intelligence is far from perfect (for instance, we tend to forget a lot). In any case, I think that autonomous robots cannot be flexible enough in complex environments without some cognitive mechanisms that we take for granted, such as the ability to memorise important aspects about the world, reason about their own actions as well as the actions of other actors in the world, or adapt their execution to a variety of contexts. From this point of view, cognitive robotics is, in my opinion, the right way to go so that we have useful autonomous robots in the long run.
• Lifelong robot learning: Unless the application domain is narrow and well-defined, I think that it is very unrealistic to expect that a robot can be fully programmed or trained before being deployed; our environments are too complex and dynamic for that to be feasible. An everyday robot should thus be able to acquire new knowledge and new skills throughout its operation. I particularly believe that lifelong learning can only be successful if it is intertwined with, on the one hand, introspection and, on the other hand, goal-directed communication with other agents (be it people or other robots), as it will otherwise be difficult to do lifelong learning efficiently. In this respect, I see introspection and learning as closely related to each other.
• Knowledge representation and reasoning: My interest in knowledge representation and reasoning is closely related to my interest in cognitive robotics and lifelong learning, and concerns the question of how predefined knowledge about the world (for example, in the form of an ontology) can be combined with and enhanced by learned representations. In particular, not all modelling frameworks are equally well-suited for being embedded into learning systems, but also not all learning representations can benefit from rich knowledge about the world that can be readily modelled, so I think that these two paradigms should be considered together in the robot development process for getting the best of both worlds.
• Simulation-based robot learning and reasoning: My specific interest here is on how a simulation can be used to allow a robot to try out its execution in scenarios that are otherwise time-consuming to set up in the real world. I think this is particularly important in the lifelong learning context, as a robot should be able to verify that the learning process is not causing performance degradation in some important aspects, such as safety.

Reviewing activities

• IEEE Transactions on Robotics (T-RO) - 2021
• Elsevier Robotics and Autonomous Systems - 2022
• ACM Computing Surveys - 2024, 2023
• IEEE Robotics and Automation Letters (RA-L) - 2024, 2023, 2022
• IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - 2024, 2023, 2022, 2020
• IEEE International Conference on Robotics and Automation (ICRA) - 2023, 2021
• IEEE International Conference on Robot & Human Interactive Communication (RO-MAN) - 2022
• International Conference on Autonomous Agents and Multiagent Systems (AAMAS) - 2021
• International Conference on Ubiquitous Robots (UR) - 2020
• RoboCup Symposium - 2024 (PC member), 2023 (PC member), 2022 (PC member)
• International Workshop on Principles of Diagnosis (DX) - 2020, 2019, 2018
• IFAC World Congress - 2020, 2017
• IFAC Symposium on Control in Transportation Systems - 2018
• International Symposium on Robotics (ISR) - 2018

Organised research events

• RSS 2024 Workshop on Robot Execution Failures and Failure Management Strategies [website]
• ICRA 2023 Workshop on Robot Execution Failures and Failure Management Strategies [website]

Professional memberships

• IEEE Robotics and Automation Society (RAS)
• IEEE RAS Technical Committee on Cognitive Robotics (2020-)
• IEEE RAS Technical Committee on Verification of Autonomous Systems (2021-)
• RoboCup@Home Technical Committee (2021-2022)