În afara temei aiqbench
Această știre a fost preluată de la o sursă pe care o urmărim, dar nu ține de domeniul AI sau cuantic, așa că nu există o perspectivă aiqbench pentru ea.
First Experimental Demonstration of Natural Hovering Extremum Seeking: A New Paradigm in Flapping Flight Physics
arXiv:2508.20836v4 Announce Type: replace Abstract: In this article, we report the first attempt of experimental validation of the recently emerged new paradigm in hovering and flapping flight physics called "Natural Hovering Extremum Seeking (NH-ES)" [doi.org/10.1103/4dm4-kc4g], which theorized that stable hovering flight physics observed in nature by flapping insects and hummingbirds can be characterized and emulated via a model-free, real-time, computationally-basic, sensory-based feedback mechanism that only needs the built-in natural oscillations of the flapping wing motion as both the control and the propulsion input. We run experiments of moth-like, light bulb source-seeking, on a flapping-wing body in a total model-free setting that is agnostic to morphological parameters and body/aerodynamic models. That is, the flapping performer (e.g., insects or hummingbirds) do not perceive internal or external governing physical equations, system states, models or parameters. Moreover, in addition to experimentally demonstrating the NH-ES paradigm in vertical motion as predicted by simulations in our earlier foundational work, we provide experiments that suggest the expansion of the NH-ES theory to longitudinal mode by yielding altitude and pitch stabilization in hovering flight. In the presented experiments, the flapper seeks, then hovers, around the light bulb source like a moth, needing only feedback of sensory measurements of light intensity taken by a simple sensor mounted on the head of the flapper body. Our experiment confirms that NH-ES needs only instantaneous, local measurement of the physical signal (e.g., light) as a feedback to perform source-seeking and does not need measurements, estimations or reference information of states, angles, altitude, or coordinates of the flapper system or source, nor does it need any global information such as access to GPS. Our results were also achieved under delay and noise effects.
Abstract:In this article, we report the first attempt of experimental validation of the recently emerged new paradigm in hovering and flapping flight physics called "Natural Hovering Extremum Seeking (NH-ES)" [this http URL], which theorized that stable hovering flight physics observed in nature by flapping insects and hummingbirds can be characterized and emulated via a model-free, real-time, computationally-basic, sensory-based feedback mechanism that only needs the built-in natural oscillations of the flapping wing motion as both the control and the propulsion input. We run experiments of moth-like, light bulb source-seeking, on a flapping-wing body in a total model-free setting that is agnostic to morphological parameters and body/aerodynamic models. That is, the flapping performer (e.g., insects or hummingbirds) do not perceive internal or external governing physical equations, system states, models or parameters. Moreover, in addition to experimentally demonstrating the NH-ES paradigm in vertical motion as predicted by simulations in our earlier foundational work, we provide experiments that suggest the expansion of the NH-ES theory to longitudinal mode by yielding altitude and pitch stabilization in hovering flight. In the presented experiments, the flapper seeks, then hovers, around the light bulb source like a moth, needing only feedback of sensory measurements of light intensity taken by a simple sensor mounted on the head of the flapper body. Our experiment confirms that NH-ES needs only instantaneous, local measurement of the physical signal (e.g., light) as a feedback to perform source-seeking and does not need measurements, estimations or reference information of states, angles, altitude, or coordinates of the flapper system or source, nor does it need any global information such as access to GPS. Our results were also achieved under delay and noise effects.
Robotics (cs.RO); Optimization and Control (math.OC)
arXiv:2508.20836 [cs.RO]
(or arXiv:2508.20836v4 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2508.20836 Focus to learn more arXiv-issued DOI via DataCite
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