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cs.RO2025

Robot Policy Transfer with Online Demonstrations: An Active Reinforcement Learning Approach

Muhan Hou, Koen Hindriks, A. E. Eiben +1

Transfer Learning (TL) is a powerful tool that enables robots to transfer learned policies across different environments, tasks, or embodiments. To further facilitate this process,…

cs.RO2025

Active Robot Curriculum Learning from Online Human Demonstrations

Muhan Hou, Koen Hindriks, A. E. Eiben +1

Learning from Demonstrations (LfD) allows robots to learn skills from human users, but its effectiveness can suffer due to sub-optimal teaching, especially from untrained demonstra…

cs.RO2025

What Can You Say to a Robot? Capability Communication Leads to More Natural Conversations

Merle M. Reimann, Koen V. Hindriks, Florian A. Kunneman +3

When encountering a robot in the wild, it is not inherently clear to human users what the robot's capabilities are. When encountering misunderstandings or problems in spoken intera…

cs.RO2024

Spectral oversubtraction? An approach for speech enhancement after robot ego speech filtering in semi-real-time

Yue Li, Koen V. Hindriks, Florian A. Kunneman

Spectral subtraction, widely used for its simplicity, has been employed to address the Robot Ego Speech Filtering (RESF) problem for detecting speech contents of human interruption…

cs.RO2024

Single-Channel Robot Ego-Speech Filtering during Human-Robot Interaction

Yue Li, Koen V Hindriks, Florian Kunneman

In this paper, we study how well human speech can automatically be filtered when this overlaps with the voice and fan noise of a social robot, Pepper. We ultimately aim for an HRI…