12 research outputs found

    Impact of Butterfly Wing-Pitch Interaction on Flight Performance

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    The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P2

    MemorZig : A Short-Term Memory-Based Algorithm for Efficient Odour Source Tracking

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    The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P8

    Investigation of Effects of Strouhal and Reynolds numbers on Propulsive Efficiency of Plunging and Pitching Foils

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    The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P2

    Impact of Butterfly Wing-Pitch Interaction on Flight Performance

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    Dropping Counter: A Detection Algorithm for Identifying Odour-Evoked Responses from Noisy Electroantennograms Measured by a Flying Robot

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    The electroantennogram (EAG) is a technique used for measuring electrical signals from the antenna of an insect. Its rapid response time, quick recovery speed, and high sensitivity make it suitable for odour-tracking tasks employing mobile robots. However, its application to flying robots has not been extensively studied owing to the electrical and mechanical noises generated. In this study, we investigated the characteristics of the EAG mounted on a tethered flying quadcopter and developed a special counter-based algorithm for detecting the odour-generated responses. As the EAG response is negative, the algorithm creates a window and compares the values inside it. Once a value is smaller than the first one, the counter will increase by one and finally turns the whole signal into a clearer odour stimulated result. By experimental evaluation, the new algorithm gives a higher cross-correlation coefficient when compared with the fixed-threshold method. The result shows that the accuracy of this novel algorithm for recognising odour-evoked EAG signals from noise exceeds that of the traditional method; furthermore, the use of insect antennae as odour sensors for flying robots is demonstrated to be feasible
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