Publikation
Uncertainty-Resilient Active Intention Recognition for Robotic Assistants
Juan Carlos Saborío; Marc Vinci; Oscar Lima; Sebastian Stock; Lennart Niecksch; Martin Günther; Alexander Sung; Joachim Hertzberg; Martin Atzmueller
In: 2025 European Conference on Mobile Robots. European Conference on Mobile Robots (ECMR-2025), September 3-5, Padua, Italy, IEEE, 2025.
Zusammenfassung
Purposeful behavior in robotic assistants requires the integration of multiple components and technological advances. Often, the problem is reduced to recognizing explicit prompts, which limits autonomy, or is oversimplified through assumptions such as near-perfect information. We argue that a critical gap remains unaddressed – specifically, the challenge of reasoning about the uncertain outcomes and perception errors inherent to human intention recognition. In response, we present a framework designed to be resilient to uncertainty and sensor noise, integrating real-time sensor data with a combination of planners. Centered around an intention-recognition POMDP, our approach addresses cooperative planning and acting under uncertainty. Our integrated framework has been successfully tested on a physical robot with promising results.