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ROSS-LAN: RObotic Sensing Simulation Scheme for Bioinspired Robotic Bird LANding

Conference paper
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Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1093)

Abstract

Aerial robotics is evolving towards the design of bioinspired platforms capable of resembling the behavior of birds and insects during flight. The development of perception algorithms for navigation of ornithopters requires sensor data information to evaluate and solve the limitations presented during the flight of these platforms. However, the payload constraints and hardware complexity of ornithopters hamper the sensor data acquisition. This paper focuses on the development of a multi-sensor simulator to retrieve the sensor information captured during the landing maneuvers of ornithopters. The landing trajectory is computed by using a bioinspired trajectory generator relying on tau theory. Further, a dataset of the sensor information records obtained during the simulation of several landing trajectories is publicly available online.

Keywords

Tau theory Ornithopter Event-based cameras LiDAR 
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Notes

Acknowledgements

This work was supported by the European Research Council as part of GRIFFIN ERC Advanced Grant 2017 (Action 788247) and the ARM-EXTEND project funded by the Spanish National RD plan (DPI2017-89790-R).

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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.GRVC-Robotics LabUniversity of SevilleSevilleSpain

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