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Nonlinear MPC for Quadrupedal Locomotion Using Second-Order Sensitivity Analysis - Presentation

Presentation for the workshop paper "Nonlinear Model Predictive Control for Quadrupedal LocomotionUsing Second-Order Sensitivity Analysis" by Dongho Kang, Flavio De Vincenti, and Stelian Coros. ICRA 2022: 6th Full-Day Workshop on Legged Robots https://leggedrobots.org 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. Project website: https://donghok.me/nmpc-for-quad-loco Computational Robotics Lab: - http://crl.ethz.ch -   / computationalr2   Dongho Kang: - https://donghok.me/ -    / donghokang   -   / eastskykang   Stelian Coros: - http://crl.ethz.ch/coros.html