Autonomous Dynamic Soaring Platform for Distributed Mobile Sensor Arrays

Boslough, M. B.

doi:10.2172/801001

Cited by 71 publications

(44 citation statements)

References 15 publications

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“…Pilots, for instance, use a combination of sensors, including magnetometers and gyroscopes to quantify their orientation during flight rather than relying on accelerometers alone (e.g. [32]). This is because the gravitational component of acceleration, as estimated by smoothing the raw data, may be affected by directional changes in velocity.…”

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confidence: 99%

Can accelerometry be used to distinguish between flight types in soaring birds?

et al. 2015

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Background: Accelerometry has been used to identify behaviours through the quantification of body posture and motion for a range of species moving in different media. This technique has not been applied to flight behaviours to the same degree, having only been used to distinguish flapping from soaring flight, even though identifying the type of soaring flight could provide important insights into the factors underlying movement paths in soaring birds. This may be due to the complexities of interpreting acceleration data, as movement in the aerial environment may be influenced by phenomena such as centripetal acceleration (pulling-g). This study used high-resolution movement data on the flight of free-living Andean condors (Vultur gryphus) and a captive Eurasian griffon vulture (Gyps fulvus) to examine the influence of gravitational, dynamic and centripetal acceleration in different flight types. Flight behaviour was categorised as thermal soaring, slope soaring, gliding and flapping, using changes in altitude and heading from magnetometry data. We examined the ability of the k-nearest neighbour (KNN) algorithm to distinguish between these behaviours using acceleration data alone. Results:Values of the vectorial static body acceleration (VeSBA) suggest that these birds experience relatively little centripetal acceleration in flight, though this varies between flight types. Centripetal acceleration appears to be of most influence during thermal soaring; consequently, it is not possible to derive bank angle from smoothed values of lateral acceleration. In contrast, the smoothed acceleration values in the dorso-ventral axis provide insight into body pitch, which varied linearly with airspeed. Classification of passive flight types via KNN was limited, with low accuracy and precision for soaring and gliding. Conclusion:The importance of soaring was evident in the high proportion of time each bird spent in this flight mode (52.17-84.00 %). Accelerometry alone was limited in its ability to distinguish between passive flight types, though smoothed values in the dorso-ventral axis did vary with airspeed. Other sensors, in particular the magnetometer, provided powerful methods of identifying flight behaviour and these data may be better suited for automated behavioural identification. This should provide further insight into the type and strength of updraughts available to soaring birds.

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Can accelerometry be used to distinguish between flight types in soaring birds?

et al. 2015

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“…Specialized references [1,3,22,23] provide a number of instances of birds in flight float and maneuver sequences, see Figure 2. According to [2,4] we have the angles (α), the force of lift (L) and speeds in soaring flight see Figures 3 and 4.…”

Section: Biological Inspiration Of Flight Flight Typesmentioning

confidence: 99%

Flight Performance of the Biological Lifting Surface

Prisacariu¹

2017

INCAS BULLETIN

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In the international research, biomimetic lifting surface are analyzed in various aspects: construction, aerodynamics and energy. The specificity of the flying wings determined similarity between the aeromechanical and the biomimetic concepts leading to numerous challenges in terms of construction, aerodynamics and actuation. The Aeromechanics of the biological flight focuses both on the various forms of lifting surfaces and the biomechanical aspects. This article contains a number of references to the biological inspiration of the morphing concept, a brief introduction to the theoretical area of the flying wings and a numerical analysis of biologically similar morphing geometry completed by conclusions and future approaches.

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“…Many of their goals are analogous to those of animals, and include migration, search, cooperation, exploration, location, and avoidance. In some cases, the adaptive behaviors of animals can be applied to the development of autonomous robots by a method we call "biomimetic behavior engineering" (Boslough 2002). Locomotion behaviors (such as dynamic soaring by albatrosses) can be analyzed and written into a control algorithm, but such purely "hand-coded" behaviors are usually unable to deal with the unexpected.…”

Section: Initial Problem Domain: Autonomous Navigationmentioning

confidence: 99%

Graduated embodiment for sophisticated agent evolution and optimization.

Pierson¹,

Peters²,

Boslough³

2005

Self Cite

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We summarize the results of a project to develop evolutionary computing methods for the design of behaviors of embodied agents in the form of autonomous vehicles. We conceived and implemented a strategy called graduated embodiment. This method allows high-level behavior algorithms to be developed using genetic programming methods in a low-fidelity, disembodied modeling environment for migration to high-fidelity, complex embodied applications. This project applies our methods to the problem domain of robot navigation using adaptive waypoints, which allow navigation behaviors to be ported among autonomous mobile robots with different degrees of embodiment, using incremental adaptation and staged optimization. Our approach to biomimetic behavior engineering is a hybrid of human design and artificial evolution, with the application of evolutionary computing in stages to preserve building blocks and limit search space. The methods and tools developed for this project are directly applicable to other agent-based modeling needs, including climate-related conflict analysis, multiplayer training methods, and market-based hypothesis evaluation.3

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Autonomous Dynamic Soaring Platform for Distributed Mobile Sensor Arrays

Cited by 71 publications

References 15 publications

Can accelerometry be used to distinguish between flight types in soaring birds?

Can accelerometry be used to distinguish between flight types in soaring birds?

Flight Performance of the Biological Lifting Surface

Graduated embodiment for sophisticated agent evolution and optimization.

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