ロボットアプリケーションにおけるBehavior TreeとFinite State Machineの生成に必要なプログラミング工数の比較
On the programming effort required to generate Behavior Trees and Finite State Machines for robotic applications
ロボットタスクの制御ポリシーをBehavior TreeとFinite State Machineで実装し、変更にかかるプログラミング工数を比較した。シミュレーションで移動マニピュレータの物品取得タスクを検証し、BTのモジュール性が工数削減に有効であることを示した。
著者: Matteo Iovino, Julian Förster, Pietro Falco, Jen Jen Chung, Roland Siegwart, Christian Smith
分類: cs.RO
原文アブストラクト
In this paper we provide a practical demonstration of how the modularity in a Behavior Tree (BT) decreases the effort in programming a robot task when compared to a Finite State Machine (FSM). In recent years the way to represent a task plan to control an autonomous agent has been shifting from the standard FSM towards BTs. Many works in the literature have highlighted and proven the benefits of such design compared to standard approaches, especially in terms of modularity, reactivity and human readability. However, these works have often failed in providing a tangible comparison in the implementation of those policies and the programming effort required to modify them. This is a relevant aspect in many robotic applications, where the design choice is dictated both by the robustness of the policy and by the time required to program it. In this work, we compare backward chained BTs with a fault-tolerant design of FSMs by evaluating the cost to modify them. We validate the analysis with a set of experiments in a simulation environment where a mobile manipulator solves an item fetching task.
