モデル予測計画法：低機動性航空機のための障害物密集環境における軌道計画
Model Predictive Planning: Trajectory Planning in Obstruction-Dense Environments for Low-Agility Aircraft
低機動性の固定翼機が障害物の多い環境を飛行するため、複数の候補経路をレイトレーシングで線形制約化し、凸二次計画で実行可能な軌道を効率的に探索するMPPを提案した。
著者: Matthew T. Wallace, Brett Streetman, Laurent Lessard
分類: eess.SY, cs.RO, cs.SY
原文アブストラクト
We present Model Predictive Planning (MPP), a trajectory planner for low-agility vehicles such as a fixed-wing aircraft to navigate obstacle-laden environments. MPP consists of (1) a multi-path planning procedure that identifies candidate paths, (2) a raytracing procedure that generates linear constraints around these paths to enforce obstacle avoidance, and (3) a convex quadratic program that finds a feasible trajectory within these constraints if one exists. Low-agility aircraft cannot track arbitrary paths, so refining a given path into a trajectory that respects the vehicle's limited maneuverability and avoids obstacles often leads to an infeasible optimization problem. The critical feature of MPP is that it efficiently considers multiple candidate paths during the refinement process, thereby greatly increasing the chance of finding a feasible and trackable trajectory. We demonstrate the effectiveness of MPP on a longitudinal aircraft model.