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.


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    Title :

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


    Additional title:

    Advs in Intelligent Syst., Computing



    Conference:

    Iberian Robotics conference ; 2019 ; Porto, Portugal November 20, 2019 - November 22, 2019



    Publication date :

    2019-11-20


    Size :

    12 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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