CollisionGAT: マルチエージェント動作のためのコントローラ非依存な一段階衝突スクリーニング
CollisionGAT: Controller-Agnostic One-Step Collision Screening for Multi-Agent Motion
移動エージェントと周囲の障害物の状態をグラフアテンションで解析し、各エージェントの衝突リスクを一度に推定する手法を提案。任意のコントローラに組み込んで経路の受理・修正・再計画に利用できる。
著者: Alan Debbas, Edwin Meriaux, Gregory Dudek
分類: cs.RO, cs.LG, cs.MA
原文アブストラクト
Before a team of robots moves, each proposed step must be checked for collisions with other robots and with obstacles. We present CollisionGAT, a graph-attention network that reads the current and proposed states of moving agents together with locally relevant stationary obstacles and returns one collision-risk score per moving agent. Any controller can use these scores to accept, repair, replan, or postpone a proposed step. We mount CollisionGAT on a continuous path-following controller and on GATeD, an obstacle-blind D* Lite planner that uses typed vetoes to update its planning graphs. Exact geometric checks supply the training labels and independently audit every executed step.