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1,321 results for “Navigator”
Data from: Terminal attack trajectories of peregrine falcons are described by the proportional navigation guidance law of missiles
The ability to intercept uncooperative targets is key to many diverse flight behaviors, from courtship to predation. Previous research has looked for simple geometric rules describing the attack trajectories of animals, but the underlying feedback laws have remained obscure. Here, we use GPS loggers and onboard video cameras to study peregrine falcons, Falco peregrinus, attacking stationary targets, maneuvering targets, and live prey. We show that the terminal attack trajectories of peregrines are not described by any simple geometric rule as previously claimed, and instead use system identification techniques to fit a phenomenological model of the dynamical system generating the observed trajectories. We find that these trajectories are best—and exceedingly well—modeled by the proportional navigation (PN) guidance law used by most guided missiles. Under this guidance law, turning is commanded at a rate proportional to the angular rate of the line-of-sight between the attacker and its target, with a constant of proportionality (i.e., feedback gain) called the navigation constant (N). Whereas most guided missiles use navigation constants falling on the interval 3 ≤ N ≤ 5, peregrine attack trajectories are best fitted by lower navigation constants (median N < 3). This lower feedback gain is appropriate at the lower flight speed of a biological system, given its presumably higher error and longer delay. This same guidance law could find use in small visually guided drones designed to remove other drones from protected airspace.
Image-Guided Navigation: A Cost Effective Practical Introduction using the Image-Guided Surgery Toolkit (IGSTK)
<p>This data was acquired as part of the work described in:"Image-Guided Navigation: A Cost Effective Practical Introduction using the Image-Guided Surgery Toolkit (IGSTK)", Ö. Güler, Z. Yaniv, Proceedings of the 34th Annual International Conference of the IEEE EMBS, 2012, <a href="https://doi.org/10.1109/EMBC.2012.6347375">doi.org/10.1109/EMBC.2012.6347375</a>.</p> <p>The data includes 10 phantom imaging studies acquired with a CT. Each of the anatomical datasets includes its CT scan, the specific details of the model, a set of anatomical landmarks localized in the CT and a picture of the plastic model. For the LEGO phantom, each dataset includes its CT scan and the instructions on how to build it.</p> <p>The executable code for simulating image-guided procedures using these phantoms and described in the manuscript is available <a href="https://yanivresearch.info/igiTutorial/igiTutorial.html">here</a>.</p> <p> </p>
NAVIGATING THE INTERSECTION
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NAVIGATING THE DIGITAL AGE
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Results from "Navigating a 10E+60" Chemical Space
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data from Enhancing Autonomous Driving through Intelligent Navigation
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Codes for "Projected Arctic shipping navigates year-round by 2100 with operational advantages along the Northern Sea Route"
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Dataset for "Brain-wide neural recordings in mice navigating physical spaces enabled by a cranial exoskeleton"
<p>Dataset for "Brain-wide neural recordings in mice navigating physical spaces enabled by a cranial exoskeleton"</p>
CRYPTOCURRENCIES AND DIGITAL CURRENCIES: NAVIGATING THE INTERSECTION OF INNOVATION AND CYBERSECURITY
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Navigating Blue Justice: Policy Gaps and Conflicts in Coastal Development from Small-Scale Fisher Perspectives
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Navigating and Querying Answer Sets: How Hard Is It Really and Why? (Empirical Case Study)
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Mars Meets Jupyter: Navigating the Interdisciplinary Divide Between Software Engineers and Domain Experts (Appendix)
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Data from: Back-tracking during navigation shows enhanced anterior cingulate activity and suppression of alpha oscillations and 'default-mode' brain activity
Successful navigation can require realising the current path choice was a mistake and the best strategy is to retreat along the recent path: 'back-tracking'. Despite the wealth of studies on the neural correlates of navigation little is known about back-tracking. To explore the neural underpinnings of back-tracking we tested humans during functional magnetic resonance imaging (fMRI) on their ability to navigate to a set of goal locations in a virtual desert island riven by lava which constrained path that could be taken. We found that on a subset of trials, participants spontaneously chose to back-track and that the majority of these choices were optimal. During back-tracking, activity increased in frontal regions and the dorsal anterior cingulate cortex, while activity was suppressed in regions associated with the core default-mode network. Using the same task, magnetoencephalography (MEG) and a separate group of participants we found that power in the alpha band was significantly decreased immediately prior to such back-tracking events. These results highlight the importance for navigation of brain networks previously identified in processing internally-generated errors and that such error-detection responses may involve shifting the brain from default-mode states to aid successful spatial orientation.
Data from: Interception by two predatory fly species is explained by a proportional navigation feedback controller
When aiming to capture a fast-moving target, animals can follow it until they catch up, or try to intercept it. In principle, interception is the more complicated strategy, but also more energy efficient. To study whether simple feedback controllers can explain interception behaviours by animals with miniature brains, we have reconstructed and studied the predatory flights of the robber fly Holcocephala fusca and killer fly Coenosia attenuata. Although both species catch other aerial arthropods out of the air, Holcocephala contrasts prey against the open sky, while Coenosia hunts against clutter and at much closer range. Thus, their solutions to this target catching task may differ significantly. We reconstructed in three dimensions the flight trajectories of these two species and those of the presented targets they were attempting to intercept. We then tested their recorded performances against simulations. We found that both species intercept targets on near time-optimal courses. To investigate the guidance laws that could underlie this behaviour, we tested three alternative control systems (pure pursuit, deviated pursuit and proportional navigation). Only proportional navigation explains the timing and magnitude of fly steering responses, but with differing gain constants and delays for each fly species. Holcocephala uses a dimensionless navigational constant of N ≈ 3 with a time delay of ≈28 ms to intercept targets over a comparatively long range. This constant is optimal, as it minimizes the control effort required to hit the target. In contrast, Coenosia uses a constant of N ≈ 1.5 with a time delay of ≈18 ms, this setting may allow Coenosia to cope with the extremely high line-of-sight rotation rates, which are due to close target proximity, and thus prevent overcompensation of steering. This is the first clear evidence of interception supported by proportional navigation in insects. This work also demonstrates how by setting different gains and delays, the same simple feedback controller can yield the necessary performance in two different environments.
Data from: Collective strategy for obstacle navigation during cooperative transport by ants
Group cohesion and consensus have primarily been studied in the context of discrete decisions, but some group tasks require making serial decisions that build on one another. We examine such collective problem solving by studying obstacle navigation during cooperative transport in ants. In cooperative transport, ants work together to move a large object back to their nest. We blocked cooperative transport groups of Paratrechina longicornis with obstacles of varying complexity, analyzing groups' trajectories to infer what kind of strategy the ants employed. Simple strategies require little information, but more challenging, robust strategies succeed with a wider range of obstacles. We found that transport groups use a stochastic strategy that leads to efficient navigation around simple obstacles, and still succeeds at difficult obstacles. While groups navigating obstacles preferentially move directly toward the nest, they change their behavior over time; the longer the ants are obstructed, the more likely they are to move away from the nest. This increases the chance of finding a path around the obstacle. Groups rapidly changed directions and rarely stalled during navigation, indicating that these ants maintain consensus even when the nest direction is blocked. Although some decisions were aided by the arrival of new ants, at many key points, direction changes were initiated within the group, with no apparent external cause. This ant species is highly effective at navigating complex environments, and implements a flexible strategy that works for both simple and more complex obstacles.
Computational and experimental insights into the chemosensory navigation of Aedes aegypti mosquito larvae
<p>Mosquitoes are prolific disease vectors that affect public health around the world. Although many studies have investigated search strategies used by host-seeking adult mosquitoes, little is known about larval search behavior. Larval behavior affects adult body size and fecundity, and thus the capacity of individual mosquitoes to find hosts and transmit disease. Understanding vector survival at all life stages is crucial for improving disease control. In this study we use experimental and computational methods to investigate the chemical ecology and search behavior of <em>Aedes aegypti</em> mosquito larvae. We first show that larvae do not respond to several olfactory cues used by adult <em>Ae. aegypti</em> to assess larval habitat quality, but perceive microbial RNA as a potent foraging attractant. Second, we demonstrate that <em>Ae. aegypti</em> larvae use chemokinesis, an unusual search strategy, to navigate chemical gradients. Finally, we use computational modeling to demonstrate that larvae respond to starvation pressure by optimizing exploration behavior - possibly critical for exploiting limited larval habitat types. Our results identify key characteristics of foraging behavior in an important disease vector mosquito. In addition to implications for better understanding and control of disease vectors, this work establishes mosquito larvae as a tractable model for chemosensory behavior and navigation.</p>
Cats and dogs: A mesopredator navigating risk and reward provisioned by an apex predator
<p>Successfully perceiving risk and reward is fundamental to the fitness of an animal, and can be achieved through a variety of perception tactics. For example, mesopredators may 'directly' perceive risk by visually observing apex predators, or may 'indirectly' perceive risk by observing habitats used by predators. Direct assessments should more accurately characterize the arrangement of risk and reward; however, indirect assessments are used more frequently in studies concerning the response of GPS-marked animals to spatiotemporally variable sources of risk and reward. We investigated the response of a mesopredator to the presence of risk and reward created by an apex predator, where risk and reward likely vary in relative perceptibility (i.e., degree of being perceptible). First, we tested whether coyotes (<em>Canis latrans</em>) use direct or indirect assessments to navigate the presence of mountain lions (<em>Puma concolor</em>; risk) and kills made by mountain lions (reward) in an area where coyotes were a common prey item for mountain lions. Second, we assessed the behavioral response of coyotes to direct encounters with mountain lions. Third, we evaluated spatiotemporal use of carrion by coyotes at kills made by mountain lions. Indirect assessments generally outperformed direct assessments when integrating analyses into a unified framework; nevertheless, our ability to detect direct perception in navigating to mountain lion kills was likely restricted by scale and sampling limitations (e.g., collar fix rates, unsampled kill sites). Rather than responding to the risk of direct encounters with mountain lions, coyotes facilitated encounters by increasing their movement rate, and engaged in risky behavior by scavenging at mountain lion kills. Coyotes appear to mitigate risk by using indirect perception to avoid mountain lions. Our predator-predator interactions and insights are nuanced and counter to the conventional predator-prey systems that have generated much of the predation risk literature.</p>
Biomechanical Effects of an Articulating Prosthetic Toe Joint During Stair Navigation for Individuals with Unilateral, Below-Knee Limb Loss
<p>See ReadMe.txt (Markdown Format)</p>
Faceted navigation of social tagging applications
<p>The goal of this paper is to conduct an analysis of seventeen existing and proposed methodologies for the use of facets in social tagging applications, with particular emphasis placed on the extent to which these methodologies address the following questions:<br> ● How do you choose facets that can apply generally to all subjects in social tagging applications<br> ● How many facets would suffice to cover site members’ needs?<br> ● Who should choose the facets?<br> ● How do you ensure that the facets chosen reflect the needs of the site members?<br> ● How do you maintain the facets and impose quality control over them?<br> Results of this analysis indicate that these methodologies provide insufficient guidelines for the choice, evaluation, and maintenance of the facets.<br> An underlying problem in many of these studies is their lack of clear definitions of what constitutes a facet. The lack of emphasis on the mutual exclusivity of facets is particularly troublesome, since it is perhaps this attribute that would determine the effectiveness of<br> facets in a social tagging application. Most of the proposed methodologies do not address how facets are to be derived or maintained.<br> A proposed framework for a more rigorous approach to the incorporation of facets into social tagging applications is presented to facilitate the use of facet analysis as a bridge between the benefits of the grassroots, bottom-up approach to the selection of tags, and a more controlled and efficient organization and visual browsing of tags in social tagging applications.</p>
Navigation data from EUT recorded at Quinta do Seixo on 04-10-2023
<p>Navigation data from EUT recorded at Quinta do Seixo on 04-10-2023</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.