核心概念
本文提出了一種名為 INSATxGCS (IxG) 的新型運動規劃算法,它結合了圖搜索和軌跡優化的優點,能夠在由凸集構成的圖形上高效地規劃機器人的運動軌跡。
统计
在 2D 迷宮環境中,圖形中有 2500 個凸集和 5198 條邊。
使用 𝜖 = 6 的 IxG* 算法的解成本略高於 GCS。
引用
"GCS is a recent method for synthesizing smooth trajectories by decomposing the planning space into convex sets, forming a graph to encode the adjacency relationships within the decomposition, and then simultaneously searching this graph and optimizing parts of the trajectory to obtain the final trajectory."
"Motivated by the observation that the trajectory solution lies only on a fraction of the set of convex sets, we present two implicit graph search methods for planning on the graph of convex sets called INSATxGCS (IxG) and IxG*."
"Numerical comparisons against GCS demonstrate the superiority of IxG across several applications, including planning for an 18-degree-of-freedom multi-arm assembly scenario."