滑らかな回避制約を備えた点群NMPC
Point-to-Cloud NMPC with Smooth Avoidance Constraints
非線形モデル予測制御を用いて、滑らかな点群距離指標と制御バリア関数により複雑な環境での目標追跡と障害物回避を実現する手法を提案した。
著者: Brener G. Ferreira, Vinicius M. Gonçalves, Marcelo A. Santos, Guilherme V. Raffo
分類: eess.SY
原文アブストラクト
This paper proposes a finite-horizon optimal control strategy for set-point tracking using a nonlinear model predictive control framework with integrated avoidance capabilities. The formulation employs a smooth point-to-cloud distance metric that ensures continuously differentiable and numerically well-conditioned gradients, even in the presence of regions with complex and nonconvex geometries. This smoothness allows safety constraints to be formulated consistently and differentiably through control barrier functions, resulting in a reliable avoidance behavior for the closed-loop system. Additionally, stationary artificial variables are introduced in the optimal control problem to preserve feasibility under changing set-points. The proposed approach is validated through numerical experiments of an aerial robot, demonstrating accurate tracking and smooth obstacle avoidance in complex environments.