Jonas Koenemann

Centre National de la Recherche Scientifique, University of Freiburg

Papers

Total Citations

452

H-Index

About

Jonas Koenemann is a leading researcher in humanoid robotics, specializing in whole-body motion generation and real-time imitation learning. His work bridges the gap between human movement and robotic control, with a focus on enabling humanoid robots to perform complex, dynamic tasks. Koenemann’s most influential contribution is his pioneering application of whole-body model-predictive control (MPC) to the HRP-2 humanoid, a breakthrough that demonstrated how permanently-updated optimal trajectories can overcome challenges like computational cost and non-linear local minima. This work, cited 228 times, is considered a landmark in achieving stable, real-time whole-body control. He is also renowned for developing systems that allow humanoids to imitate human motions in real time, using compact models that prioritize end-effector positions and center-of-mass tracking. His 2014 paper on this topic, with 167 citations, and his earlier work on the NAO humanoid (57 citations) have set standards for human-robot interaction and motion transfer. Koenemann’s research has profound implications for assistive robotics, entertainment, and autonomous systems, making him a key figure in advancing humanoid capabilities toward seamless, human-like movement.