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Flying insects track turbulent odor plumes to find mates, food and egg-laying sites. To maintain contact with the plume, insects are thought to adapt their flight control according to the distribution of odor in the plume using the timing of odor onsets and intervals between odor encounters. Although timing cues are important, few studies have addressed whether insects are capable of deriving spatial information about odor distribution from bilateral comparisons between their antennae in flight. The proboscis extension reflex (PER) associative learning protocol, originally developed to study odor learning in honeybees, was used as a tool to ask if hawkmoths, Manduca sexta, can discriminate between odor stimuli arriving on either antenna. We show moths discriminated the odor arrival side with an accuracy of >70%. Information about spatial distribution of odor stimuli may be available to moths searching for odor sources, opening the possibility that they use both spatial and temporal odor information. This article has an associated First Person interview with the first author of the paper.

Although often considered a nondominant sense for spatial perception, chemosensory perception can be used to localize the source of an event and potentially help us navigate through our environment. Would blind people who lack the dominant spatial sense—vision—develop enhanced spatial chemosensation or suffer from the lack of visual calibration on spatial chemosensory perception? To investigate this question, we tested odorant localization abilities across nostrils in blind people compared to sighted controls and if the time of vision loss onset modulates those abilities. We observed that congenitally blind individuals (10 subjects) outperformed sighted (20 subjects) and late-blind subjects (10 subjects) in a birhinal localization task using mixed olfactory-trigeminal stimuli. This advantage in congenitally blind people was selective to olfactory localization but not observed for odorant detection or identification. We, therefore, showed that congenital blindness but not blindness acquired late in life is linked to enhanced localization of chemosensory stimuli across nostrils, most probably of the trigeminal component. In addition to previous studies highlighting enhanced localization abilities in auditory and tactile modalities, our current results extend such enhanced abilities to chemosensory localization. [ABSTRACT FROM AUTHOR]

In this paper, we consider the problem of Active Source Identification in steady-state advection–diffusion (AD) transport systems. Unlike existing bioinspired heuristic methods, we propose a model-based approach that employs the AD–partial differential equation (PDE) to capture the transport phenomenon. Specifically, we formulate the source identification (SI) problem as a PDE-constrained optimization problem in function spaces. To obtain a tractable solution, we reduce the dimension of the concentration field using Proper Orthogonal Decomposition and approximate the unknown source field using nonlinear basis functions, drastically decreasing the number of unknowns. Moreover, to collect the concentration measurements, we control a robot sensor through a sequence of waypoints that maximize the smallest eigenvalue of the Fisher Information matrix of the unknown source parameters. Specifically, after every new measurement, an SI problem is solved to obtain a source estimate that is used to determine the next waypoint. We show that our algorithm can efficiently identify sources in complex AD systems and nonconvex domains, in simulation and experimentally. This is the first time that PDEs are used for robotic SI in practice. [ABSTRACT FROM AUTHOR]

Rodents can localize odor sources by comparing odor inputs to the right and left nostrils. However, the neuronal circuits underlying such odor localization are not known. We recorded neurons in the anterior olfactory nucleus (AON) while administering odors to the ipsilateral or contralateral (ipsi- or contra-) nostril. Neurons in the AON pars externa (AONpE) showed respiration phase-locked excitatory spike responses to ipsinostril-only stimulation with a category of odorants, and inhibitory responses to contranostril-only stimulation with the same odorants. Simultaneous odor stimulation of the ipsi- and contranostrils elicited significantly smaller responses than ipsinostril-only stimulation, indicating that AONpE neurons subtract the contranostril odor inputs from ipsinostril odor inputs. An ipsilateral odor source induced larger responses than a centrally located source, whereas an odor source at the contralateral position elicited inhibitory responses. These results indicate that individual AONpE neurons can distinguish the right or left position of an odor source by referencing signals from the two nostrils. [ABSTRACT FROM AUTHOR]

Abstract: Previous work on robotic odour localisation in enclosed environments, relying on an airflow model, has faced significant limitations due to the fact that large differences between airflow topologies are predicted for only small variations in a physical map. This is due to uncertainties in the map and approximations in the modelling process. Furthermore, there are uncertainties regarding the flow direction through inlet/outlet ducts. We present a method for dealing with these uncertainties through the generation of multiple airflow hypotheses. As the robot performs odour localisation, airflow in the environment is measured and used to adjust the confidences of the hypotheses using Bayesian inference. The best hypothesis is then selected, which allows the completion of the localisation task. Experimental results show that this method is capable of improving the robustness of odour localisation in the presence of uncertainties, where previously it was incapable. The results further demonstrate the usefulness of naïve physics for practical robotics applications. [Copyright &y& Elsevier]

Robotic odor localization has become a prominent research area in recent years. It promises many valuable practical applications, and contributes to the knowledge of biological odor localization, which has in many cases been the source of inspiration. There have been a diversity of approaches, implemented in both simulated and practical experiments, with a wide variety of platforms, and in a number of environments. This article presents a survey of the existing methods, which have been organized into taxonomic classifications. This provides a framework in which to evaluate the methods, view how they relate to each other, and make qualitative comparisons. The methods are grouped at the highest level by environmental conditions, and then by the localization method which in most cases is closely associated with the type of sensors used. [ABSTRACT FROM AUTHOR]

This paper presents an investigation of odor localization by groups of autonomous mobile robots. First, we describe a distributed algorithm by which groups of agents can solve the full odor localization task. Next, we establish that conducting polymer-based odor sensors possess the combination of speed and sensitivity necessary to enable real world odor plume tracing and we demonstrate that simple local position, odor, and flow information, tightly coupled with robot behavior, is sufficient to allow a robot to localize the source of an odor plume. Finally, we show that elementary communication among a group of agents can increase the efficiency of the odor localization system performance. [ABSTRACT FROM PUBLISHER]

Olfactory navigation is defined as a task of a self-propelled navigator with some sensors capabilities to detect odor (or scalar concentration) convected and diffused in a windy environment. Known for their expertise in locating an odor source, male moths feature a bio-inspirational model of olfactory navigation using chemosensory. Many studies have developed moths-inspired algorithms based on proposed strategies of odor-sourcing. However, comparing among various bio-inspired strategies is challenging, due to the lack of a componential framework that allows statistical comparison of their performances, in a controlled environment. This work aims at closing this gap, using an open source, freely accessible simulation framework. To demonstrate the applicability of our simulated framework as a benchmarking tool, we implemented two different moth-inspired navigation strategies; for each strategy, specific modifications in the navigation module were carried out, resulting in four different navigation models. We tested the performance of moth-like navigators of these models through various wind and odor spread parameters in a virtual turbulent environment. The performance of the navigators was comprehensively analyzed using bio-statistical tests. This benchmark-ready simulation framework could be useful for the biology-oriented, as well as engineering-oriented studies, assisting in deducing the evolutionary efficient strategies and improving self-propelled autonomous systems in complex environments.•The open-source framework `Mothpy' provides a computational platform that simulates the behavior of moth-like navigators, using two main inputs to be modified by the user: (1) flow condition; and (2) navigation strategy.•`Mothpy' can be used as a benchmarking platform to compare the performance of multiple moth-like navigators, under various physical environments, and different searching strategies.•Method name: Mothpy 0.0.1' - an open-source moth-inspired navigator simulator., (© 2021 The Authors. Published by Elsevier B.V.)

Flying insects track turbulent odor plumes to find mates, food and egg-laying sites. To maintain contact with the plume, insects are thought to adapt their flight control according to the distribution of odor in the plume using the timing of odor onsets and intervals between odor encounters. Although timing cues are important, few studies have addressed whether insects are capable of deriving spatial information about odor distribution from bilateral comparisons between their antennae in flight. The proboscis extension reflex (PER) associative learning protocol, originally developed to study odor learning in honeybees, was used as a tool to ask if hawkmoths, Manduca sexta, can discriminate between odor stimuli arriving on either antenna. We show moths discriminated the odor arrival side with an accuracy of >70%. Information about spatial distribution of odor stimuli may be available to moths searching for odor sources, opening the possibility that they use both spatial and temporal odor information.This article has an associated First Person interview with the first author of the paper., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2021. Published by The Company of Biologists Ltd.)