非構造動的環境における衝突回避のためのモデル予測輪郭制御
Model Predictive Contouring Control for Collision Avoidance in Unstructured Dynamic Environments
静的・動的障害物がある非構造環境で、参照経路への追従誤差を最小化しつつ障害物を回避する局所軌道をオンライン生成するMPCCベースの手法を提案し、人混みの屋内で移動ロボット実験を行った。
著者: Bruno Brito, Boaz Floor, Laura Ferranti, Javier Alonso-Mora
分類: cs.RO
原文アブストラクト
This paper presents a method for local motion planning in unstructured environments with static and moving obstacles, such as humans. Given a reference path and speed, our optimization-based receding-horizon approach computes a local trajectory that minimizes the tracking error while avoiding obstacles. We build on nonlinear model-predictive contouring control (MPCC) and extend it to incorporate a static map by computing, online, a set of convex regions in free space. We model moving obstacles as ellipsoids and provide a correct bound to approximate the collision region, given by the Minkowsky sum of an ellipse and a circle. Our framework is agnostic to the robot model. We present experimental results with a mobile robot navigating in indoor environments populated with humans. Our method is executed fully onboard without the need of external support and can be applied to other robot morphologies such as autonomous cars.
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