Robohub.org
 

Interview with Amar Halilovic: Explainable AI for robotics


by
10 June 2025



share this:

In this interview series, we’re meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. The Doctoral Consortium provides an opportunity for a group of PhD students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. In this latest interview, we hear from Amar Halilovic, a PhD student at Ulm University.

Tell us a bit about your PhD – where are you studying, and what is the topic of your research?

I’m currently a PhD student at Ulm University in Germany, where I focus on explainable AI for robotics. My research investigates how robots can generate explanations of their actions in a way that aligns with human preferences and expectations, particularly in navigation tasks.

Could you give us an overview of the research you’ve carried out so far during your PhD?

So far, I’ve developed a framework for environmental explanations of robot actions and decisions, especially when things go wrong. I have explored black-box and generative approaches for the generation of textual and visual explanations. Furthermore, I have been working on planning of different explanation attributes, such as timing, representation, duration, etc. Lately, I’ve been working on methods for dynamically selecting the best explanation strategy depending on the context and user preferences.

Is there an aspect of your research that has been particularly interesting?

Yes, I find it fascinating how people interpret robot behavior differently depending on the urgency or failure context. It’s been especially rewarding to study how explanation expectations shift in different situations and how we can tailor explanation timing and content accordingly.

What are your plans for building on your research so far during the PhD – what aspects will you be investigating next?

Next, I’ll be extending the framework to incorporate real-time adaptation, enabling robots to learn from user feedback and adjust their explanations on the fly. I’m also planning more user studies to validate the effectiveness of these explanations in real-world human-robot interaction settings.

Amar with his poster at the AAAI/SIGAI Doctoral Consortium at AAAI 2025.

What made you want to study AI, and, in particular, explainable robot navigation?

I’ve always been interested in the intersection of humans and machines. During my studies, I realized that making AI systems understandable isn’t just a technical challenge—it’s key to trust and usability. Robot navigation struck me as a particularly compelling area because decisions are spatial and visual, making explanations both challenging and impactful.

What advice would you give to someone thinking of doing a PhD in the field?

Pick a topic that genuinely excites you—you’ll be living with it for several years! Also, build a support network of mentors and peers. It’s easy to get lost in the technical work, but collaboration and feedback are vital.

Could you tell us an interesting (non-AI related) fact about you?

I have lived and studied in four different countries.

About Amar

Amar is a PhD student at the Institute of Artificial Intelligence of Ulm University in Germany. His research focuses on Explainable Artificial Intelligence (XAI) in Human-Robot Interaction (HRI), particularly how robots can generate context-sensitive explanations for navigation decisions. He combines symbolic planning and machine learning to build explainable robot systems that adapt to human preferences and different contexts. Before starting his PhD, he studied Electrical Engineering at the University of Sarajevo in Sarajevo, Bosnia and Herzegovina, and Computer Science at Mälardalen University in Västerås, Sweden. Outside academia, Amar enjoys travelling, photography, and exploring connections between technology and society.




AIhub is a non-profit dedicated to connecting the AI community to the public by providing free, high-quality information in AI.
AIhub is a non-profit dedicated to connecting the AI community to the public by providing free, high-quality information in AI.





Related posts :



#RoboCup2025: social media round-up 1

  21 Jul 2025
Find out what participants got up to during the opening days of RoboCup2025 in Salvador, Brazil.

Livestream of RoboCup2025

  18 Jul 2025
Watch the competition live from Salvador!

Tackling the 3D Simulation League: an interview with Klaus Dorer and Stefan Glaser

and   15 Jul 2025
With RoboCup2025 starting today, we found out more about the 3D simulation league, and the new simulator they have in the works.

An interview with Nicolai Ommer: the RoboCupSoccer Small Size League

and   01 Jul 2025
We caught up with Nicolai to find out more about the Small Size League, how the auto referees work, and how teams use AI.

RoboCupRescue: an interview with Adam Jacoff

and   25 Jun 2025
Find out what's new in the RoboCupRescue League this year.

Robot Talk Episode 126 – Why are we building humanoid robots?

  20 Jun 2025
In this special live recording at Imperial College London, Claire chatted to Ben Russell, Maryam Banitalebi Dehkordi, and Petar Kormushev about humanoid robotics.

Gearing up for RoboCupJunior: Interview with Ana Patrícia Magalhães

and   18 Jun 2025
We hear from the organiser of RoboCupJunior 2025 and find out how the preparations are going for the event.

Robot Talk Episode 125 – Chatting with robots, with Gabriel Skantze

  13 Jun 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Gabriel Skantze from KTH Royal Institute of Technology about having natural face-to-face conversations with robots.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


©2025.05 - Association for the Understanding of Artificial Intelligence


 












©2025.05 - Association for the Understanding of Artificial Intelligence