狭い空間を歩く：双対性最適化による四足ロボットの安全クリティカルな歩行制御
Walking in Narrow Spaces: Safety-critical Locomotion Control for Quadrupedal Robots with Duality-based Optimization
四足ロボットが狭い空間を安全に自律移動できるよう、指数型離散制御バリア関数と双対性に基づく障害物回避制約を非線形モデル予測制御と全身制御に統合した枠組みを提案した。
著者: Qiayuan Liao, Zhongyu Li, Akshay Thirugnanam, Jun Zeng, Koushil Sreenath
分類: cs.RO
原文アブストラクト
This paper presents a safety-critical locomotion control framework for quadrupedal robots. Our goal is to enable quadrupedal robots to safely navigate in cluttered environments. To tackle this, we introduce exponential Discrete Control Barrier Functions (exponential DCBFs) with duality-based obstacle avoidance constraints into a Nonlinear Model Predictive Control (NMPC) with Whole-Body Control (WBC) framework for quadrupedal locomotion control. This enables us to use polytopes to describe the shapes of the robot and obstacles for collision avoidance while doing locomotion control of quadrupedal robots. Compared to most prior work, especially using CBFs, that utilize spherical and conservative approximation for obstacle avoidance, this work demonstrates a quadrupedal robot autonomously and safely navigating through very tight spaces in the real world. (Our open-source code is available at github.com/HybridRobotics/quadruped_nmpc_dcbf_duality, and the video is available at youtu.be/p1gSQjwXm1Q.)
