ARC@ORU Transparent Robot Decision-Making with Interpretable & Explainable Methods
05 december 2025 13:30 – 14:30 Visual Lab, ARC, Örebro universitet
This talk within the ARC@ORU Research Seminar Series explores how interpretable and explainable AI can make robotic decision-making transparent and trustworthy.
Transparent Robot Decision-Making with Interpretable & Explainable Methods
Speaker: Dr. Karinne Ramirez-Amaro, Associate professor with the Division of Systems and Control (SYSCON), Department of Electrical Engineering (E2) at Chalmers University of Technology
Venue: Visual Lab, ARC, or remotely by Zoom
Please register further down on this page!
About the seminar
Transparent decision-making enables humans to understand, interpret, and predict what robots do. Interpretable and explainable methods enhance transparency: interpretable methods clarify how a learned model reaches decisions, while explainable methods articulate why specific decisions were made. In this talk, I will first introduce our interpretable AI methods that generate compact, general semantic models to infer human activities, enabling robots to gain a high-level understanding of human movement. Next, I will present our causal approach, which enables robots to rapidly predict and prevent both immediate and future failures, helping them understand why failures occur, learn from mistakes, and improve future performance. Finally, I will discuss how we combine these methods into a single framework that integrates symbolic planning with hierarchical reinforcement learning. This integration allows us to learn flexible, reusable robot policies for manipulation tasks, yielding coherent sequences of actions that can be executed independently. Interpretable and explainable AI are key to developing general-purpose robots. These approaches enable robots to make complex decisions in dynamic and unpredictable environments.
Bio
Dr. Karinne Ramirez-Amaro is a Docent/Associate professor with the Division of Systems and Control (SYSCON), Department of Electrical Engineering (E2) at Chalmers University of Technology since April 2022. In 2019, she became an Assistant professor at Chalmers in the research group Mechatronics. Previously, she was a post-doctoral researcher at the Chair for Cognitive Systems (ICS) at the Technical University of Munich (TUM). She completed her Ph.D. (summa cum laude) at the Department of Electrical and Computer Engineering at the Technical University of Munich (TUM), Germany in 2015. From October 2009 until Dec 2012, she was a member of the Intelligent Autonomous Systems (IAS) group headed by Prof. Michael Beetz. She received a Master degree in Computer Science (with honours) at the Center for Computing Research of the National Polytechnic Institute (CIC-IPN) in Mexico City, Mexico in 2007.