Insect-inspired navigation algorithm for an aerial agent using satellite imagery

Humans have long marveled at the ability of animals to navigate swiftly, accurately, and across long distances. Many mechanisms have been proposed for how animals acquire, store, and retrace learned routes, yet many of these hypotheses appear incongruent with behavioral observations and the animals' neural constraints. The "Navigation by Scene Familiarity Hypothesis" proposed originally for insect navigation offers an elegantly simple solution for retracing previously experienced routes without the need for complex neural architectures and memory retrieval mechanisms. This hypothesis proposes that an animal can return to a target location by simply moving toward the most familiar scene at any given point. Proof of concept simulations have used computer-generated ant's-eye views of the world, but here we test the ability of scene familiarity algorithms to navigate training routes across satellite images extracted from Google Maps. We find that Google satellite images are so rich in visual information that familiarity algorithms can be used to retrace even tortuous routes with low-resolution sensors. We discuss the implications of these findings not only for animal navigation but also for the potential development of visual augmentation systems and robot guidance algorithms.

Insect vision: emergence of pattern recognition from coarse encoding

Neurogenetic tools of Drosophila research allow unique access to the neural circuitry underpinning visually guided behaviours. New research is highlighting how particular areas in the fly's central brain needed for pattern recognition provide a coarse visual encoding.

Desert ants locate food by combining high sensitivity to food odors with extensive crosswind runs

Desert ants feeding on dead arthropods forage for food items that are distributed unpredictably in space and time in the food-scarce terrain of the Saharan salt pans [1]. Scavengers of the genus Cataglyphis forage individually and do not lay pheromone trails [2]. They rely primarily on path integration [3] for navigation and, in addition, use visual [4] and olfactory cues [5-7]. While most studies have focused on the navigational mechanisms of ants targeting a familiar place like the nest or a learned feeding site, little is known about how ants locate food in their natural environment. Here we show that Cataglyphis fortis is highly sensitive to and attracted by food odors, especially the necromone linoleic acid, enabling them to locate tiny arthropods over several meters in distance. Furthermore, during the search for food, ants use extensive crosswind walks that increase the chances of localizing food plumes. By combining high sensitivity toward food odors with crosswind runs, the ants efficiently screen the desert for food and hence reduce the time spent foraging in their harsh desert environment.

Developing clinical decision support within a commercial electronic health record system to improve antimicrobial prescribing in the neonatal ICU

OBJECTIVE

To develop and implement a clinical decision support (CDS) tool to improve antibiotic prescribing in neonatal intensive care units (NICUs) and to evaluate user acceptance of the CDS tool.

METHODS

Following sociotechnical analysis of NICU prescribing processes, a CDS tool for empiric and targeted antimicrobial therapy for healthcare-associated infections (HAIs) was developed and incorporated into a commercial electronic health record (EHR) in two NICUs. User logs were reviewed and NICU prescribers were surveyed for their perceptions of the CDS tool.

RESULTS

The CDS tool aggregated selected laboratory results, including culture results, to make treatment recommendations for common clinical scenarios. From July 2010 to May 2012, 1,303 CDS activations for 452 patients occurred representing 22% of patients prescribed antibiotics during this period. While NICU clinicians viewed two culture results per tool activation, prescribing recommendations were viewed during only 15% of activations. Most (63%) survey respondents were aware of the CDS tool, but fewer (37%) used it during their most recent NICU rotation. Respondents considered the most useful features to be summarized culture results (43%) and antibiotic recommendations (48%).

DISCUSSION

During the study period, the CDS tool functionality was hindered by EHR upgrades, implementation of a new laboratory information system, and changes to antimicrobial testing methodologies. Loss of functionality may have reduced viewing antibiotic recommendations. In contrast, viewing culture results was frequently performed, likely because this feature was perceived as useful and functionality was preserved.

CONCLUSION

To improve CDS tool visibility and usefulness, we recommend early user and information technology team involvement which would facilitate use and mitigate implementation challenges.

Visual scanning behaviours and their role in the navigation of the Australian desert ant Melophorus bagoti

Ants are excellent navigators, using a combination of innate strategies and learnt information to guide habitual routes. The mechanisms underlying this behaviour are little understood though one avenue of investigation is to explore how innate sensori-motor routines are used to accomplish route navigation. For instance, Australian desert ant foragers are occasionally observed to cease translation and rotate on the spot. Here, we investigate this behaviour using high-speed videography and computational analysis. We find that scanning behaviour is saccadic with pauses separated by fast rotations. Further, we have identified four situations where scanning is typically displayed: (1) by naïve ants on their first departure from the nest; (2) by experienced ants departing from the nest for their first foraging trip of the day; (3) by experienced ants when the familiar visual surround was experimentally modified, in which case frequency and duration of scans were proportional to the degree of modification; (4) when the information from visual cues is at odds with the direction indicated by the ant's path integration system. Taken together, we see a general relationship between scanning behaviours and periods of uncertainty.

Scene perception and the visual control of travel direction in navigating wood ants

This review reflects a few of Mike Land's many and varied contributions to visual science. In it, we show for wood ants, as Mike has done for a variety of animals, including readers of this piece, what can be learnt from a detailed analysis of an animal's visually guided eye, head or body movements. In the case of wood ants, close examination of their body movements, as they follow visually guided routes, is starting to reveal how they perceive and respond to their visual world and negotiate a path within it. We describe first some of the mechanisms that underlie the visual control of their paths, emphasizing that vision is not the ant's only sense. In the second part, we discuss how remembered local shape-dependent and global shape-independent features of a visual scene may interact in guiding the ant's path.

Strength of shock-loaded single-crystal tantalum [100] determined using in situ broadband x-ray Laue diffraction

The strength of shock-loaded single crystal tantalum [100] has been experimentally determined using in situ broadband x-ray Laue diffraction to measure the strain state of the compressed crystal, and elastic constants calculated from first principles. The inferred strength reaches 35 GPa at a shock pressure of 181 GPa and is in excellent agreement with a multiscale strength model [N. R. Barton et al., J. Appl. Phys. 109, 073501 (2011)], which employs a hierarchy of simulation methods over a range of length scales to calculate strength from first principles.

Snapshots in ants? New interpretations of paradigmatic experiments

Ants can use visual information to guide long idiosyncratic routes and accurately pinpoint locations in complex natural environments. It has often been assumed that the world knowledge of these foragers consists of multiple discrete views that are retrieved sequentially for breaking routes into sections controlling approaches to a goal. Here we challenge this idea using a model of visual navigation that does not store and use discrete views to replicate the results from paradigmatic experiments that have been taken as evidence that ants navigate using such discrete snapshots. Instead of sequentially retrieving views, the proposed architecture gathers information from all experienced views into a single memory network, and uses this network all along the route to determine the most familiar heading at a given location. This algorithm is consistent with the navigation of ants in both laboratory and natural environments, and provides a parsimonious solution to deal with visual information from multiple locations.

View-based matching can be more than image matching: The importance of considering an animal's perspective

Using vision for navigation is important for many animals and a common debate is the extent to which spatial performance can be explained by "simple" view-based matching strategies. We discuss, in the context of recent work, how confusion between image-matching algorithms and the broader class of view-based navigation strategies, is hindering the debate around the use of vision in spatial cognition. A proper consideration of view-based matching strategies requires an understanding of the visual information available to a given animal within a particular experiment.

A model of ant route navigation driven by scene familiarity

In this paper we propose a model of visually guided route navigation in ants that captures the known properties of real behaviour whilst retaining mechanistic simplicity and thus biological plausibility. For an ant, the coupling of movement and viewing direction means that a familiar view specifies a familiar direction of movement. Since the views experienced along a habitual route will be more familiar, route navigation can be re-cast as a search for familiar views. This search can be performed with a simple scanning routine, a behaviour that ants have been observed to perform. We test this proposed route navigation strategy in simulation, by learning a series of routes through visually cluttered environments consisting of objects that are only distinguishable as silhouettes against the sky. In the first instance we determine view familiarity by exhaustive comparison with the set of views experienced during training. In further experiments we train an artificial neural network to perform familiarity discrimination using the training views. Our results indicate that, not only is the approach successful, but also that the routes that are learnt show many of the characteristics of the routes of desert ants. As such, we believe the model represents the only detailed and complete model of insect route guidance to date. What is more, the model provides a general demonstration that visually guided routes can be produced with parsimonious mechanisms that do not specify when or what to learn, nor separate routes into sequences of waypoints.

A model of ant route navigation driven by scene familiarity

In this paper we propose a model of visually guided route navigation in ants that captures the known properties of real behaviour whilst retaining mechanistic simplicity and thus biological plausibility. For an ant, the coupling of movement and viewing direction means that a familiar view specifies a familiar direction of movement. Since the views experienced along a habitual route will be more familiar, route navigation can be re-cast as a search for familiar views. This search can be performed with a simple scanning routine, a behaviour that ants have been observed to perform. We test this proposed route navigation strategy in simulation, by learning a series of routes through visually cluttered environments consisting of objects that are only distinguishable as silhouettes against the sky. In the first instance we determine view familiarity by exhaustive comparison with the set of views experienced during training. In further experiments we train an artificial neural network to perform familiarity discrimination using the training views. Our results indicate that, not only is the approach successful, but also that the routes that are learnt show many of the characteristics of the routes of desert ants. As such, we believe the model represents the only detailed and complete model of insect route guidance to date. What is more, the model provides a general demonstration that visually guided routes can be produced with parsimonious mechanisms that do not specify when or what to learn, nor separate routes into sequences of waypoints.

How might ants use panoramic views for route navigation?

Studies of insect navigation have demonstrated that insects possess an interesting and sophisticated repertoire of visual navigation behaviours. Ongoing research seeks to help us understand how these behaviours are controlled in natural complex environments. A necessary complement to behavioural studies is an understanding of the sensory ecology within which an animal behaves. To this end we have analysed ants'-perspective views of a habitat within which desert ant navigation is well studied. Results from our analysis suggest that: parsimonious visual strategies for homing and route guidance are effective over behaviourally useful distances even in cluttered environments; that these strategies can function effectively using only the skyline heights as input; and that the simplicity and efficacy of using stored views as a visual compass makes it a viable and robust mechanism for route guidance.