超複雑地形もOK!自動運転をもっと賢くする技術の研究だよ✨
● 3D地形(山とか都会)に対応してるのがスゴくない?😳 ● 既存の手法より100倍も速くなったんだって!🚀 ● 安全運転のために、キッチリ計算してるってことね😎
背景 自動運転(じどううんてん)って、安全第一じゃん? でも、道って平らじゃないし、速度制限とかあるよね? この研究は、車(くるま)が色んな条件を守りながら、最短ルートで目的地に着く方法を考えてるんだって!🤯
方法 3Dメッシュ地形(さんでぃーめっしゅちけい)っていう、めっちゃ細かい地形データを使って、車の動きを計算してるんだって! Mixed-Integer Kinodynamic (MIKD) Plannerっていうスゴイやつを使って、速く計算できるように工夫してるらしい!🧐
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This work casts the kinodynamic planning problem for car-like vehicles as an optimization task to compute a minimum-time trajectory and its associated velocity profile, subject to boundary conditions on velocity, acceleration, and steering. The approach simultaneously optimizes both the spatial path and the sequence of acceleration and steering controls, ensuring continuous motion from a specified initial position and velocity to a target end position and velocity.The method analyzes the admissible control space and terrain to avoid local minima. The proposed method operates efficiently in simplicial complex environments, a preferred terrain representation for capturing intricate 3D landscapes. The problem is initially posed as a mixed-integer fractional program with quadratic constraints, which is then reformulated into a mixed-integer bilinear objective through a variable transformation and subsequently relaxed to a mixed-integer linear program using McCormick envelopes. Comparative simulations against planners such as MPPI and log-MPPI demonstrate that the proposed approach generates solutions 104 times faster while strictly adhering to the specified constraints