MINOS is a simulator suitable for developing multi-sensor models for goal-oriented navigation in complex indoor environments. The simulator leverages large datasets of complex 3D environments and supports flexible configuration of multimodal sensor suites. The dataset benchmarks deep learning-based navigation methods, analyzes the impact of environmental complexity on navigation performance, and conducts a comparative study of multimodality in sensor kinematic learning.

Citation

@article{savva2017minos,
author = {Manolis Savva and Angel X. Chang and Alexey Dosovitskiy and Thomas Funkhouser and Vladlen Koltun},
title = {{MINOS}: Multimodal Indoor Simulator for Navigation in Complex Environments},
journal = {arXiv:1712.03931},
year = {2017}
}