Christian Kirches
Papers
5
Total Citations
175
H-Index
4
About
Christian Kirches is a leading researcher at the intersection of numerical optimization and humanoid robotics, specializing in real-time Nonlinear Model Predictive Control (NMPC) and optimal control for whole-body motion generation. His most impactful work, "A Reactive Walking Pattern Generator Based on Nonlinear Model Predictive Control" (97 citations), demonstrated that NMPC can be implemented on position-controlled humanoid robots, enabling "walking without thinking" by simultaneously considering position and dynamics. Kirches further advanced the field with his work on multi-contact motion generation (42 citations), providing a complete solution for computing fully-dynamic motions that generalize bipedal locomotion. His contributions extend to benchmarking model-free versus model-based optimal control (28 citations) and developing efficient derivative evaluation methods for rigid-body dynamics with kinematic constraints (6 citations). Notably, Kirches has also explored combining multi-level real-time iterations of NMPC to realize complex squatting motions on the Leo robot. His work bridges the gap between theoretical optimization and practical robotic control, enabling more agile and autonomous humanoid robots. With over 175 total citations, Kirches continues to push the boundaries of real-time optimal control for complex mechanical systems.
Research Focus
Key Achievements
Top Papers
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- 3Benchmarking model-free and model-based optimal control28 citations · 2017
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