統合されたタスク・動作計画
Integrated Task and Motion Planning
物体が多い環境でロボットが移動と物体操作を行うTAMP問題を定義し、連続空間の部分問題の解法と離散・連続要素の統合手法の観点から既存アルゴリズムを分類・概観したサーベイ論文。
著者: Caelan Reed Garrett, Rohan Chitnis, Rachel Holladay, Beomjoon Kim, Tom Silver, Leslie Pack Kaelbling, Tomás Lozano-Pérez
分類: cs.RO, cs.AI
原文アブストラクト
The problem of planning for a robot that operates in environments containing a large number of objects, taking actions to move itself through the world as well as to change the state of the objects, is known as task and motion planning (TAMP). TAMP problems contain elements of discrete task planning, discrete-continuous mathematical programming, and continuous motion planning, and thus cannot be effectively addressed by any of these fields directly. In this paper, we define a class of TAMP problems and survey algorithms for solving them, characterizing the solution methods in terms of their strategies for solving the continuous-space subproblems and their techniques for integrating the discrete and continuous components of the search.
