凸実行可能集合アルゴリズムによる実時間動作計画最適化
The Convex Feasible Set Algorithm for Real Time Optimization in Motion Planning
障害物による非凸制約下でも高速に解ける凸実行可能集合アルゴリズム(CFS)を提案し、移動ロボットの動作計画に適用して有効性をシミュレーションで示した論文。
著者: Changliu Liu, Chung-Yen Lin, Masayoshi Tomizuka
分類: math.OC, cs.RO
原文アブストラクト
With the development of robotics, there are growing needs for real time motion planning. However, due to obstacles in the environment, the planning problem is highly non-convex, which makes it difficult to achieve real time computation using existing non-convex optimization algorithms. This paper introduces the convex feasible set algorithm (CFS) which is a fast algorithm for non-convex optimization problems that have convex costs and non-convex constraints. The idea is to find a convex feasible set for the original problem and iteratively solve a sequence of subproblems using the convex constraints. The feasibility and the convergence of the proposed algorithm are proved in the paper. The application of this method on motion planning for mobile robots is discussed. The simulations demonstrate the effectiveness of the proposed algorithm.
