Multi-Robot Coverage and Exploration using Spatial Graph Neural Networks
Multi-Robot Coverage and Exploration using Spatial Graph Neural Networks
复制标题
使用空间图神经网络的多机器人覆盖和探索
DOI：
10.1109/iros51168.2021.9636675
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发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Alejandro Ribeiro
中科院分区：
文献类型：
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作者：
Ekaterina V. Tolstaya;James Paulos;Vijay R. Kumar;Alejandro Ribeiro
The multi-robot coverage problem is an essential building block for systems that perform tasks like inspection, exploration, or search and rescue. We discretize the coverage problem to induce a spatial graph of locations and represent robots as nodes in the graph. Then, we train a Graph Neural Network controller that leverages the spatial equivariance of the task to imitate an expert open-loop routing solution. This approach generalizes well to much larger maps and larger teams that are intractable for the expert. In particular, the model generalizes effectively to a simulation of ten quadrotors and dozens of buildings in an urban setting. We also demonstrate the GNN controller can surpass planning-based approaches in an exploration task.
