2023-12-02-akcin23a.md

title	section	openreview	abstract	layout	series	publisher	issn	id	month	tex_title	firstpage	lastpage	page	order	cycles	bibtex_author	author	date	address	container-title	volume	genre	issued	pdf	extras
Fleet Active Learning: A Submodular Maximization Approach	Poster	low-53sFqn	In multi-robot systems, robots often gather data to improve the performance of their deep neural networks (DNNs) for perception and planning. Ideally, these robots should select the most informative samples from their local data distributions by employing active learning approaches. However, when the data collection is distributed among multiple robots, redundancy becomes an issue as different robots may select similar data points. To overcome this challenge, we propose a fleet active learning (FAL) framework in which robots collectively select informative data samples to enhance their DNN models. Our framework leverages submodular maximization techniques to prioritize the selection of samples with high information gain. Through an iterative algorithm, the robots coordinate their efforts to collectively select the most valuable samples while minimizing communication between robots. We provide a theoretical analysis of the performance of our proposed framework and show that it is able to approximate the NP-hard optimal solution. We demonstrate the effectiveness of our framework through experiments on real-world perception and classification datasets, which include autonomous driving datasets such as Berkeley DeepDrive. Our results show an improvement by up to $25.0 %$ in classification accuracy, $9.2 %$ in mean average precision and $48.5 %$ in the submodular objective value compared to a completely distributed baseline.	inproceedings	Proceedings of Machine Learning Research	PMLR	2640-3498	akcin23a	0	Fleet Active Learning: A Submodular Maximization Approach	1378	1399	1378-1399	1378	false	Akcin, Oguzhan and Unuvar, Orhan and Ure, Onat and Chinchali, Sandeep P.	given family Oguzhan Akcin given family Orhan Unuvar given family Onat Ure given family Sandeep P. Chinchali	2023-12-02		Proceedings of The 7th Conference on Robot Learning	229	inproceedings	date-parts 2023 12 2	https://proceedings.mlr.press/v229/akcin23a/akcin23a.pdf