Exploration-RRT: A multi-objective Path Planning and Exploration Framework for Unknown and Unstructured Environments.

被引:27
作者
Lindqvist, Bjorn [1 ]
Agha-Mohammadi, Ali-Akbar [2 ]
Nikolakopoulos, George [1 ]
机构
[1] Lulea Univ Technol, Dept Comp Elect & Space Engn, Robot & Artificial Intelligence Team, SE-97187 Lulea, Sweden
[2] CALTECH, Jet Prop Lab, 4800 Oak Grove Dr, Pasadena, CA 91109 USA
来源
2021 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) | 2021年
基金
欧盟地平线“2020”;
关键词
D O I
10.1109/IROS51168.2021.9636243
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article establishes the Exploration-RRT algorithm: A novel general-purpose combined exploration and path planning algorithm, based on a multi-goal Rapidly-Exploring Random Trees (RRT) framework. Exploration-RRT (ERRT) has been specifically designed for utilization in 3D exploration missions, with partially or completely unknown and unstructured environments. The novel proposed ERRT is based on a multi-objective optimization framework and it is able to take under consideration the potential information gain, the distance travelled, and the actuation costs, along trajectories to pseudo-random goals, generated from considering the on-board sensor model and the non-linear model of the utilized platform. In this article, the algorithmic pipeline of the ERRT will be established and the overall applicability and efficiency of the proposed scheme will be presented on an application with an Unmanned Aerial Vehicle (UAV) model, equipped with a 3D lidar, in a simulated operating environment, with the goal of exploring a completely unknown area as efficiently and quickly as possible.
引用
收藏
页码:3429 / 3435
页数:7
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