Adaptive-Resolution Cooperative Field Mapping With Event-Triggered Distributed Map Fusion
Tianyi Ding, Ronghao Zheng, Senlin Zhang, Meiqin Liu
Abstract
Cooperative scalar field mapping is an important task for multi-robot systems. However, the limited communication and computation resources of robots have hindered the application of cooperative field mapping in large-scale scenarios. This letter proposes an adaptive-resolution Gaussian process mapping with event-triggered distributed map fusion to overcome these resource limitations. A novel event-triggered communication mechanism is proposed for distributed map fusion under range-limited communication. A resolution adaptation method is developed to balance the mapping computation, communication resources, and accuracy. A closed-form approximated information metric is derived for faster map resolution optimization. Finally, the performances of the proposed algorithms are validated by real online light field mapping experiments.
BibTeX
@inproceedings{ral2025_adaptiveresoluti,
title = {Adaptive-Resolution Cooperative Field Mapping With Event-Triggered Distributed Map Fusion},
author = {Tianyi Ding and Ronghao Zheng and Senlin Zhang and Meiqin Liu},
booktitle = {RA-L 2025},
year = {2025}
}