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Static Is Not Enough: A Comparative Study of VR and SpaceMouse in Static and Dynamic Teleoperation Tasks
Yijun Zhou, Muhan Hou, Kim Baraka
Imitation learning relies on high-quality demonstrations, and teleoperation is a primary way to collect them, making teleoperation interface choice crucial for the data. Prior work…
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,…
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…
A Multi-Behavior Planning Framework for Robot Guide
Muhan Hou, Zonghao Mu, Jing Li +2
The guiding task of a mobile robot requires not only human-aware navigation, but also appropriate yet timely interaction for active instruction. State-of-the-art tour-guide models…