Litcius/Paper detail

Cafe-Mpc: A Cascaded-Fidelity Model Predictive Control Framework With Tuning-Free Whole-Body Control

He Li, Patrick M. Wensing

2024IEEE Transactions on Robotics20 citationsDOI

Abstract

This work introduces an optimization-based planning and control framework for real-time synthesis of whole-body motions for legged robots. At the core of the proposed framework is a cascaded-fidelity model predictive controller (<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cafe-Mpc</small>). <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cafe-Mpc</small> strategically relaxes the planning problem along the prediction horizon (i.e., with descending model fidelity, increasingly coarse time steps, and relaxed constraints) for computational and performance gains. This problem is numerically solved with an efficient customized multiple-shooting iLQR solver that is tailored for hybrid systems. The action-value function from <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cafe-Mpc</small> is then used as the basis for a new value-function-based whole-body control (VWBC) technique that avoids additional tuning. In this respect, the proposed framework unifies whole-body MPC and more conventional whole-body quadratic programming, which have been treated as separate components in previous works. We study the effects of the cascaded relaxations in <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cafe-Mpc</small> on the tracking performance and required computation time. We also show that <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cafe-Mpc</small>, if configured appropriately, advances the performance of whole-body MPC without necessarily increasing computational cost. Furthermore, we show the superior performance of VWBC over a conventional Riccati feedback controller in terms of constraint handling. The proposed framework enables accomplishing a gymnastic-style running barrel roll for the first time on quadruped hardware, where <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Cafe-Mpc</small> runs at 50 Hz, and the solver spends on average 5.3 ms per iteration. Results are demonstrated in the accompanying video.

Topics & Concepts

Model predictive controlControl theory (sociology)Control (management)Computer scienceFidelityControl engineeringEngineeringArtificial intelligenceTelecommunicationsAdvanced Control Systems OptimizationCardiovascular Function and Risk FactorsReal-Time Systems Scheduling