Abstract
Insects have—over millions of years of evolution—perfected many of the systems that roboticists aim to achieve; they can swiftly and robustly navigate through different environments under various conditions while at the same time being highly energy efficient. To reach this level of performance and efficiency, one might want to look at and take inspiration from how these insects achieve their feats. Currently, no dataset exists that allows bio-inspired navigation models to be evaluated over long >100 m real-life routes. We present a novel dataset containing omnidirectional event vision, frame-based vision, depth frames, inertial measurement (IMU) readings, and centimeter-accurate GNSS positioning over kilometer long stretches in and around the TUDelft campus. The dataset is used to evaluate familiarity-based insect-inspired neural navigation models on their performance over longer sequences. It demonstrates that current scene familiarity models are not suited for long-ranged navigation, at least not in their current form.
Original language | English |
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Title of host publication | Biomimetic and Biohybrid Systems - 11th International Conference, Living Machines 2022, Proceedings |
Editors | Alexander Hunt, Vasiliki Vouloutsi, Kenneth Moses, Roger Quinn, Anna Mura, Tony Prescott, Paul F. Verschure |
Publisher | Springer |
Pages | 279-291 |
Number of pages | 13 |
ISBN (Print) | 9783031204692 |
DOIs | |
Publication status | Published - 2022 |
Event | 11th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2022 - Virtual, Online Duration: 19 Jul 2022 → 22 Jul 2022 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13548 LNAI |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 11th International Conference on Biomimetic and Biohybrid Systems, Living Machines 2022 |
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City | Virtual, Online |
Period | 19/07/22 → 22/07/22 |
Bibliographical note
Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-careOtherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Keywords
- Event-based camera
- GNSS
- GPS
- Long-range navigation
- Neuromorphic systems
- RGB Camera