Supplementary video for the ArXiv paper,
"Nonlinear Model Predictive Control for Quadrupedal Locomotion Using Second-Order Sensitivity Analysis" by Dongho Kang, Flavio De Vincenti, and Stelian Coros.
Presented in ICRA 2022: 6th Full-day Workshop on Legged Robots
Abstract:
We present a versatile nonlinear model predictive control (NMPC) approach for quadrupedal locomotion. Our formulation can jointly optimize a base trajectory and a set of stepping locations over a finite time horizon based on simplified dynamics models. We leverage second-order sensitivity analysis and a sparse Gauss-Newton (SGN) method to solve the resulting optimal control problems. We further document our ongoing effort to verify our approach through simulation and hardware experiments. Finally, we extend our locomotion framework to deal with challenging tasks that comprise gap crossing, movement on stepping stones, and multi-robot control.
Acknowledgment:
This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 866480.)
Project website:
donghok.me/nmpc-for-quad-loco/
Computational Robotics Lab:
- crl.ethz.ch/
- / computationalr2
Dongho Kang
- donghok.me/
- / donghokang
- / eastskykang
Stelian Coros
- crl.ethz.ch/coros.html