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Combining Local and Global Perception for Autonomous Navigation on Nano-UAVs

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European Robotics Forum 2024 (ERF 2024)

Part of the book series: Springer Proceedings in Advanced Robotics ((SPAR,volume 32))

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Abstract

A critical challenge in deploying unmanned aerial vehicles (UAVs) for autonomous tasks is their ability to navigate in an unknown environment. This paper introduces a novel vision-depth fusion approach for autonomous navigation on nano-UAVs. We combine the visual-based PULP-Dronet [1] convolutional neural network for semantic information extraction, i.e., serving as the global perception, with 8\(\times \)8 px depth maps for close-proximity maneuvers, i.e., the local perception. When tested in-field, our integration strategy highlights the complementary strengths of both visual and depth sensory information. We achieve a 100% success rate over 15 flights in a complex navigation scenario, encompassing straight pathways, static obstacle avoidance, and 90\(^\circ \) turns.

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Notes

  1. 1.

    https://youtu.be/J703fo_zIKQ.

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Acknowledgments

We thank D. Palossi and D. Christodoulou for their contribution to this work.

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Correspondence to Lorenzo Lamberti .

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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Lamberti, L., Rutishauser, G., Conti, F., Benini, L. (2024). Combining Local and Global Perception for Autonomous Navigation on Nano-UAVs. In: Secchi, C., Marconi, L. (eds) European Robotics Forum 2024. ERF 2024. Springer Proceedings in Advanced Robotics, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-031-76424-0_51

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