Task Decomposition and Multi-Robot Task Allocation in Exploration with Bayesian Networks

被引：0

作者：

Chuang, Ching-Wei ^{[1
]}

Lin, Wei-Yu ^{[1
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Taipei, Taiwan

来源：

2024 EIGHTH IEEE INTERNATIONAL CONFERENCE ON ROBOTIC COMPUTING, IRC 2024 | 2024年

关键词：

Autonomous Exploration; Unknown Environments; Multi-Robot Task Allocation; Task Decomposition; Bayesian Networks;

D O I：

10.1109/IRC63610.2024.00018

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Although exploration methods for homogeneous multi-robot systems have improved, they generally lack consideration for the impact of robot capabilities on exploration in complex environments. To address this, we propose a task-allocation method based on Bayesian Networks for decentralized heterogeneous systems. Tasks are randomly distributed in unexplored areas, guiding robots to complete the exploration. Our method is demonstrated in real-world ground environments.

引用

页码：80 / 83

页数：4

共 15 条

[1] Multi-robot exploration in task allocation problem [J].