Shinde, Kashmira and Lee, Jongseok and Humt, Matthias and Sezgin, Aydin and Triebel, Rudolph (2020) Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry. In: Workshop on AI for Autonomous Driving (AIAD), the 37th International Conference on Machine Learning (ICML). Workshop on AI for Autonomous Driving (AIAD), the 37 th International Conference on Machine Learning (ICML), Vienna, Austria.
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Abstract
This paper presents an end-to-end multi-modal learning approach for monocular Visual-Inertial Odometry (VIO), which is specifically designed to exploit sensor complementarity in the light of sensor degradation scenarios. The proposed network makes use of a multi-head self-attention mechanism that learns multiplicative interactions between multiple streams of information. Another design feature of our approach is the incorporation of the model uncertainty using scalable Laplace Approximation. We evaluate the performance of the proposed approach by comparing it against the end-to-end state-of-the-art methods on the KITTI dataset and show that it achieves superior performance. Importantly, our work thereby provides an empirical evidence that learning multiplicative interactions can result in a powerful inductive bias for increased robustness to sensor failures.
Item URL in elib: | https://elib.dlr.de/135547/ | ||||||||||||||||||||||||
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Document Type: | Conference or Workshop Item (Other) | ||||||||||||||||||||||||
Title: | Learning Multiplicative Interactions with Bayesian Neural Networks for Visual-Inertial Odometry | ||||||||||||||||||||||||
Authors: |
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Date: | 13 July 2020 | ||||||||||||||||||||||||
Journal or Publication Title: | Workshop on AI for Autonomous Driving (AIAD), the 37th International Conference on Machine Learning (ICML) | ||||||||||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||||||||||
Open Access: | Yes | ||||||||||||||||||||||||
Gold Open Access: | No | ||||||||||||||||||||||||
In SCOPUS: | No | ||||||||||||||||||||||||
In ISI Web of Science: | No | ||||||||||||||||||||||||
Status: | Published | ||||||||||||||||||||||||
Keywords: | Multimodal learning, Autonomous Driving, Visual-Inertial Odometry, Robot Perception, Machine Learning, Deep Learning | ||||||||||||||||||||||||
Event Title: | Workshop on AI for Autonomous Driving (AIAD), the 37 th International Conference on Machine Learning (ICML) | ||||||||||||||||||||||||
Event Location: | Vienna, Austria | ||||||||||||||||||||||||
Event Type: | Workshop | ||||||||||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||||||
HGF - Program: | Space | ||||||||||||||||||||||||
HGF - Program Themes: | Space System Technology | ||||||||||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||||||||||
DLR - Program: | R SY - Space System Technology | ||||||||||||||||||||||||
DLR - Research theme (Project): | R - Vorhaben Intelligente Mobilität (old), Vorhaben Intelligente Mobilität (old) | ||||||||||||||||||||||||
Location: | Oberpfaffenhofen | ||||||||||||||||||||||||
Institutes and Institutions: | Institute of Robotics and Mechatronics (since 2013) Institute of Robotics and Mechatronics (since 2013) > Perception and Cognition | ||||||||||||||||||||||||
Deposited By: | Lee, Jongseok | ||||||||||||||||||||||||
Deposited On: | 21 Jul 2020 09:46 | ||||||||||||||||||||||||
Last Modified: | 20 Jul 2022 14:35 |
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