Path planning for Indoor Partially Unknown Environment Exploration and Mapping

被引：0
|
作者：
Zakiev, Aufar [1 ]
Lavrenov, Roman [1 ]
Magid, Evgeni [1 ]
Indelman, Vadim [2 ]
机构：
[1] Kazan Fed Univ, Higher Inst Informat Technol & Informat Syst ITIS, Intelligent Robot Syst Lab, 35 Kremlyovskaya St, Kazan 420008, Russia
[2] Technion Israel Inst Technol, Autonomous Nav & Percept Lab, Haifa, Israel
来源：
ICAROB 2018: PROCEEDINGS OF THE 2018 INTERNATIONAL CONFERENCE ON ARTIFICIAL LIFE AND ROBOTICS | 2018年
基金：
俄罗斯基础研究基金会;
关键词：
robotics; algorithm; modelling; mapping; ROS/Gazebo; indoor exploration; path planning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper addresses a problem of partially unknown environment exploration and mapping. The proposed path planning algorithm provides global and local goals search taking into account limited sensing range and visibility constraints that arise from obstacles. Looking for local goals near a global path maximizes robot utility and helps avoiding returns to regions with low potential gain. All stages were tested in ROS/Gazebo simulations and results were compared with a naive algorithm that was proposed earlier.
引用
收藏
页码：399 / 402
页数：4
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