Towards Odor-Sensitive Mobile Robots

Abstract

Out of all the components of a mobile robot, its sensorial system is undoubtedly among the most critical ones when operating in real environments. Until now, these sensorial systems mostly relied on range sensors (laser scanner, sonar, active triangulation) and cameras. While electronic noses have barely been employed, they can provide a complementary sensory information, vital for some applications, as with humans. This chapter analyzes the motivation of providing a robot with gas-sensing capabilities and also reviews some of the hurdles that are preventing smell from achieving the importance of other sensing modalities in robotics. The achievements made so far are reviewed to illustrate the current status on the three main fields within robotics olfaction: the classification of volatile substances, the spatial estimation of the gas dispersion from sparse measurements, and the localization of the gas source within a known environment.

Towards Odor-Sensitive Mobile Robots

“…Furthermore, like in the case of a network of fixed enose, the calibration and drift compensation of the sensors composing the e-nose is also an important drawback to consider. In this regard, works like (De Vito, Massera, Piga, Martinotto, & Di Francia, 2008;Esposito et al, 2016) have presented different approaches to cross-calibrate different e-noses without the need to perform a tedious and costly laboratory calibration. These proposals are indeed fundamental when the MRO system is to be deployed for long times (drift and ageing), or when multiple mobile e-noses are set up simultaneously (Hasenfratz, 2015).…”

“…Related to environmental monitoring applications, there are works where a gas measuring device sensing the air quality is carried by a person (Zappi, Bales, Park, Griswold, & Šimuni, 2012), a bike (Elen et al, 2013;, public transport vehicles (Hasenfratz et al, 2015) or even drones (Neumann, Bartholmai, Schiller, Wiggerich, & Manolov, 2010;Pobkrut, Eamsa-ard, & Kerdcharoen, 2016). Despite sampling the environment in motion, most of the works does not perform a classification phase to discriminate the type of gas, but rather employs an array of gas sensors with disjoint selectivity (i.e.…”

“…First, a mobile robot usually carries only one e-nose, therefore a more sophisticated and powerful (and more expensive) model can be used, enabling the analysis of more complex compounds and the detection of faster changes in the gas concentration (Gonzalez-Jimenez, Monroy, Garcia, & Blanco, 2011;Ishida, Kobayashi, Nakamoto, & Moriizumi, 1999;Werle et al, 2002). The calibration phase of the sensing devices is greatly simplified because of the reduced number of e-noses, something that represents an important issue in large gas sensing networks (Esposito et al, 2016). Also, MRO systems permit sampling at higher (and adaptive) resolutions, while still providing the required accurate localization of each measurement.…”

An Evaluation of Plume Tracking as a Strategy for Gas Source Localization in Turbulent Wind Flows

“…Proposed strategies include Braitenberg approaches [2] or algorithms based on E. coli bacteria [3], to cite some. Performance was then improved by combining chemotaxis with anemotaxis, exploiting the strong directional cue that the flow direction brings when acting under turbulent flows [4]. Proposed methods include the dung beetle or zigzag method, which involves moving upwind within the This work has been funded by the Spanish Government (project DPI2017-84827-R) and the Andalusia Government (project TEP2012-530), both with funds from the European Union (FEDER).…”

“…Yet, as reported by [8], the main drawback of these strategies arises when facing realistic, turbulent environments. Under this challenging environmental conditions, the plume is not straight and continuous, but given the time-varying nature of flow fields and the predominance of turbulence over diffusion, plumes tend to meander, become patchy and, to a far lesser extent, spread out [4]. Furthermore, the plume structure can change over time if the direction of air flow shifts considerably, being difficult to accurately determining the wind flow direction.…”