核貯蔵環境における豊富な情報マップを用いた自律ロボットナビゲーション
Autonomous Robot Navigation with Rich Information Mapping in Nuclear Storage Environments
核施設内の点検作業を無人地上車両(UGV)が自律的に行うため、障害物配置と点検対象物の位置・向きを含むリッチ情報マップを生成し、その情報で巡回優先度を決めてナビゲーションする手法を提案した論文。
著者: Maozhen Wang, Xianchao Long, Peng Chang, Taskin Padir
分類: cs.RO
原文アブストラクト
This paper presents our approach to develop a method for an unmanned ground vehicle (UGV) to perform inspection tasks in nuclear environments using rich information maps. To reduce inspectors' exposure to elevated radiation levels, an autonomous navigation framework for the UGV has been developed to perform routine inspections such as counting containers, recording their ID tags and performing gamma measurements on some of them. In order to achieve autonomy, a rich information map is generated which includes not only the 2D global cost map consisting of obstacle locations for path planning, but also the location and orientation information for the objects of interest from the inspector's perspective. The UGV's autonomy framework utilizes this information to prioritize locations to navigate to perform the inspections. In this paper, we present our method of generating this rich information map, originally developed to meet the requirements of the International Atomic Energy Agency (IAEA) Robotics Challenge. We demonstrate the performance of our method in a simulated testbed environment containing uranium hexafluoride (UF6) storage container mock ups.
