特異点回避を備えたユニサイクルロボットの軌道追従のための緩和二次計画法に基づくフレームワーク
A Relaxed Quadratic-Program-based Framework for Trajectory Tracking of Unicycle Robots with Singularity Avoidance
ユニサイクルロボットの軌道追従で問題となる動的フィードバック線形化の特異点を、スラック変数を持つ二次計画法で回避する手法を提案し、TurtleBot3でシミュレーション検証した。
著者: Hamza Tariq, Usman Ali, Adeel Akhtar
分類: cs.RO, eess.SY, math.OC
原文アブストラクト
Dynamic feedback linearization (DFL) is a classical technique for trajectory tracking of unicycle-type mobile robots, but the resulting DFL-based controller becomes singular when the linear velocity vanishes, rendering standard DFL-based controllers unsuitable for stop-and-reverse maneuvers. This paper proposes a quadratic-program (QP)-based optimal control framework that avoids this singularity, while establishing local Lipschitz continuity of the resulting feedback law. Our approach reformulates the DFL constraints as an equality-constrained QP with a slack variable, ensuring feasibility for all states and reference signals, including at points where the robot's velocity vanishes. By introducing slack variables and tunable parameters, we demonstrate that the singular configuration can be avoided for a large class of reference trajectories. The effectiveness of the proposed approach for trajectory tracking is demonstrated through ROS 2-Gazebo simulations on a TurtleBot3 Waffle robot. The code is available at https://gradslab.github.io/DFL_QP_Unicycle/