Person:
Sponberg, Simon

Permanent Link
https://hdl.handle.net/1853/71726
Associated Organization(s)
Organizational Unit
Organizational Unit
Organizational Unit
ORCID
https://orcid.org/0000-0003-4942-4894
ArchiveSpace Name Record

Filters

2014 - 2019 1 2020 - 2023 3
3 1
1
4
4
Reset filters

Settings

Publication Search Results

Now showing 1 - 4 of 4
  • No Thumbnail Available
    Item
    Raw data for article: "Moth resonant mechanics are tuned to wingbeat frequency and energetic demands"
    (Georgia Institute of Technology, 2023-12) Wold, Ethan ; Aiello, Brett ; Harris, Manon ; bin Sikandar, Usama ; Lynch, James ; Gravish, Nick ; Sponberg, Simon
    An insect’s wingbeat frequency is a critical determinant of its flight performance and varies by multiple orders of magnitude across Insecta. Despite potential energetic and kine-matic benefits for an insect that matches its wingbeat frequency to its resonant frequency, recent work has shown that moths may operate off of their resonant peak. We hypothesized that across species, wingbeat frequency scales with resonance frequency to maintain favorable energetics, but with an offset in species that use frequency modulation as a means of flight control. The moth superfamily Bombycoidea is ideal for testing this hypothesis because their wingbeat frequencies vary across species by an order of magnitude, despite similar morphology and actuation. We used materials testing, high-speed videography, and a “spring-wing” model of resonant aerodynamics to determine how components of an insect’s flight apparatus (thoracic properties, wing inertia, muscle strain, and aerodynamics) vary with wingbeat frequency. We find that the resonant frequency of a moth correlates with wingbeat frequency, but resonance curve shape (described by the Weis-Fogh number) and peak location vary within the clade in a way that corresponds to frequency-dependent biomechanical demands. Our results demonstrate that a suite of adaptations in muscle, exoskeleton and wing drive variation in resonant mechanics, reflecting potential constraints on matching wingbeat and resonant frequencies.
  • No Thumbnail Available
    Item
    Raw mechanical testing data for article "Structural damping renders the hawkmoth exoskeleton mechanically insensitive to non-sinusoidal deformations"
    (Georgia Institute of Technology, 2023) Wold, Ethan S. ; Lynch, James ; Gravish, Nick ; Sponberg, Simon
  • No Thumbnail Available
    Item
    Raw physiology data for article "Biophysical transitions in insect flight dynamics are bridged by common muscle physiology"
    (Georgia Institute of Technology, 2022) Sponberg, Simon ; Gau, Jeff ; Lynch, James ; Aiello, Brett ; Wold, Ethan ; Gravish, Nick
  • No Thumbnail Available
    Item
    The Science Behind Animal-Inspired Robotics
    (Georgia Institute of Technology, 2014-11-10) Sponberg, Simon
    The 21st Century has seen an explosion of bio-inspired technology and devices. Perhaps no where has this approach been more transformative than in the field of mobile robotics. Geckos, snakes, and even cockroaches have motivated new sticky, stable, steerable robots. Yet inspiration means more than curiosity. As scientists we must unravel the scientific principles and mechanisms underlying animal performance. By studying the physics of these living systems we can inform a systematic approach to animal-inspired robotics. By doing so, we discover new properties and dynamics of complex systems -- the robots themselves even become experimental platforms to test hypotheses. We can learn the pitfalls of ignoring the evolutionary context that shaped animal locomotion and the power of non-dimensional ratios that scale across biology. In this talk, we will first explore how human technology is taking on more characteristics for which the natural world is a better teacher. We will then use several examples over the past decade of robotics research where animals have served as the inspiration, but where identification of the underlying physics has led to innovation. Finally we will discuss how new bio-physical insights emerged from studying the resulting robots as physical models for the biological systems.