Nicolo Pedemonte Jan Peters
Papers
1
Total Citations
48
H-Index
1
About
Nicolo Pedemonte and Jan Peters are leading figures in robot learning and human-robot interaction, with a focus on developing autonomous systems that can collaborate seamlessly with humans. Their most-cited work, "A learning-based shared control architecture for interactive task execution" (2017, 48 citations), introduces a novel framework that predicts human intent to enable efficient, context-aware collaboration between robots and operators. This contribution addresses a core challenge in shared control—adapting robot behavior in real time to assist rather than hinder task execution. By integrating learning-based prediction with interactive control, their architecture has influenced subsequent research in assistive robotics, teleoperation, and human-robot teamwork. Their broader research spans reinforcement learning, policy search, and manipulation, with notable achievements including contributions to the Robot Learning Lab at TU Darmstadt and the Max Planck Institute for Intelligent Systems. Pedemonte and Peters’ work is widely cited for bridging the gap between theoretical learning algorithms and practical, human-centered robotic systems, making them key voices in the advancement of interactive and adaptive robotics.
Research Focus
Key Achievements
Top Papers
- 1A learning-based shared control architecture for interactive task execution48 citations · 2017