Lightweight Semantic Mesh Mapping for Autonomous Vehicles

Herb M, Weiherer T, Navab N, Tombari F (2021)

Publication Type: Conference contribution

Publication year: 2021

Journal

Proceedings - IEEE International Conference on Robotics and Automation Institute of Electrical and Electronics Engineers

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2021-May

Pages Range: 6732-6738

Conference Proceedings Title: Proceedings - IEEE International Conference on Robotics and Automation

Event location: Xi'an, CHN

ISBN: 9781728190778

DOI: 10.1109/ICRA48506.2021.9560996

Abstract

Lightweight and semantically meaningful environment maps are crucial for many applications in robotics and autonomous driving to facilitate higher-level tasks such as navigation and planning. In this paper we present a novel approach to incrementally build a meaningful and lightweight semantic map directly as a 3D mesh from a monocular or stereo sequence. Our system leverages existing feature-based visual odometry paired with learned depth prediction and semantic image segmentation to identify and reconstruct semantically relevant environment structure. We introduce a probabilistic fusion scheme to incrementally refine and extend a 3D mesh with semantic labels for each face without intermediate voxel-based fusion. To demonstrate its effectiveness, we evaluate our system in outdoor driving scenarios with monocular depth prediction and stereo and present quantitative and qualitative reconstruction results with comparison to ground truth. Our results show that the proposed approach achieves reconstruction quality comparable to current state-of-the-art voxel-based methods while being much more lightweight both in storage and computation.

Involved external institutions

Audi AG DE Germany (DE) Technische Universität München (TUM) DE Germany (DE)

How to cite

APA:

Herb, M., Weiherer, T., Navab, N., & Tombari, F. (2021). Lightweight Semantic Mesh Mapping for Autonomous Vehicles. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 6732-6738). Xi'an, CHN: Institute of Electrical and Electronics Engineers Inc..

MLA:

Herb, Markus, et al. "Lightweight Semantic Mesh Mapping for Autonomous Vehicles." Proceedings of the 2021 IEEE International Conference on Robotics and Automation, ICRA 2021, Xi'an, CHN Institute of Electrical and Electronics Engineers Inc., 2021. 6732-6738.

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