高速な接触陰的モデル予測制御
Fast Contact-Implicit Model-Predictive Control
接触の生成・消滅を扱う接触陰的MPCを提案し、LCP定式化と専用の内点法ソルバで高速化、四足ロボットの実機で非周期的動作の生成・追従を実証した。
著者: Simon Le Cleac'h, Taylor Howell, Shuo Yang, Chi-Yen Lee, John Zhang, Arun Bishop, Mac Schwager, Zachary Manchester
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
We present a general approach for controlling robotic systems that make and break contact with their environments. Contact-implicit model predictive control (CI-MPC) generalizes linear MPC to contact-rich settings by utilizing a bi-level planning formulation with lower-level contact dynamics formulated as time-varying linear complementarity problems (LCPs) computed using strategic Taylor approximations about a reference trajectory. These dynamics enable the upper-level planning problem to reason about contact timing and forces, and generate entirely new contact-mode sequences online. To achieve reliable and fast numerical convergence, we devise a structure-exploiting interior-point solver for these LCP contact dynamics and a custom trajectory optimizer for the tracking problem. We demonstrate real-time solution rates for CI-MPC and the ability to generate and track non-periodic behaviours in hardware experiments on a quadrupedal robot. We also show that the controller is robust to model mismatch and can respond to disturbances by discovering and exploiting new contact modes across a variety of robotic systems in simulation, including a pushbot, planar hopper, planar quadruped, and planar biped.
