Theoretical analysis of three bio-inspired plume tracking algorithms

Lochmatter, Thomas; Martinoli, Alcherio

doi:10.1109/robot.2009.5152686

Cited by 40 publications

(26 citation statements)

References 26 publications

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“…Attempts were also made to find the optimal upwind plume-tracking algorithm by comparing variations of algorithms by theoretical analysis, simulations, and experiments [24,33,35,62,63]. However, it is difficult at this moment to derive general conclusions from such work since different research groups are working with different robots in different environments.…”

Section: Attempts To Improve Gas Source Localization Robotsmentioning

confidence: 99%

Using Chemical Sensors as “Noses” for Mobile Robots

Ishida

Lilienthal

Matsukura

et al. 2016

Essentials of Machine Olfaction and Taste

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Section: Attempts To Improve Gas Source Localization Robotsmentioning

confidence: 99%

Using Chemical Sensors as “Noses” for Mobile Robots

Ishida

Lilienthal

Matsukura

et al. 2016

Essentials of Machine Olfaction and Taste

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“…This is an idealization of devices such as sensors of chemical concentration, sensors of wi-fi strength, and other sensors that transduce the intensity of a local spatially-varying field. (Lochmatter and Martinoli, 2009;Gutmann, Brisson, Eade, Fong, and Munich, 2010).…”

Section: A Ideal Field-samplersmentioning

confidence: 99%

Bootstrapping bilinear models of Simple Vehicles

Censi

Murray

2015

The International Journal of Robotics Research

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Abstract-Learning and adaptivity will play a large role in robotics in the future. Two questions that are open: 1) in principle, how much it is possible to learn; and, 2) in practice, how much should an agent be able to learn. The bootstrapping scenario describes the extreme case in which agents need to learn "everything" from scratch, including a torque-to-pixels model for its robotic body. This paper considers the bootstrapping problem for a subset of the set of all robots. The Simple Vehicles are idealization of mobile robots equipped with a set of "canonical" exteroceptive sensors: the camera, the rangefinder and the field sampler. The sensorimotor dynamics of these sensors are derived and shown to be surprising similar. These sensorimotor dynamics are well approximated by a class of nonlinear systems that assume an instantaneous bilinear relation among observations, commands, and changes in the observations. The bilinear approximation is sufficient to guarantee success in the task of generalized "servoing": driving the observations to a given goal snapshot. Simulations and experiments substantiate the theoretical results. This is the first instance of a bootstrapping agent that can learn the model of the dynamics of a relatively large universe of systems and use the models to solve well-defined tasks, with no parameter tuning or hand-designed features.

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“…The comparison is carried out both in simulation [63], with experiments carried out in a wind tunnel with real robots [64] and even theoretically under simplifying assumptions [65]. The algorithms are compared in terms of success rate and distance overhead when tracking the plume up to the source.…”

Section: Gas Source Localizationmentioning

confidence: 99%

Gas Discrimination for Mobile Robots

Trincavelli

2011

Künstl Intell

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The problem addressed in this thesis is discrimination of gases with an array of partially selective gas sensors. Metal oxide gas sensors are the most common gas sensing technology since they have, compared to other gas sensing technologies, a high sensitivity to the target compounds, a fast response time, they show a good stability of the response over time and they are commercially available. One of the most severe limitation of metal oxide gas sensors is the scarce selectivity, that means that they do not respond only to the compound for which they are optimized but also to other compounds. One way to enhance the selectivity of metal oxide gas sensors is to build an array of sensors with different, and partially overlapping, selectivities and then analyze the response of the array with a pattern recognition algorithm. The concept of an array of partially selective gas sensors used together with a pattern recognition algorithm is known as an electronic nose (e-nose).In this thesis the attention is focused on e-nose applications related mobile robotics. A mobile robot equipped with an e-nose can address tasks like environmental monitoring, search and rescue operations or exploration of hazardous areas. In e-noses mounted on mobile robots the sensing array is most often directly exposed to the environment without the use of a sensing chamber. This choice is often made because of constraints in weight, costs and because the dynamic response obtained by the direct interaction of the sensors with the gas plume contains valuable information. However, this setup introduces additional challenges due to the gas dispersion that characterize natural environments. Turbulent and chaotic gas dispersal causes the array of sensors to be exposed to rapid changes in concentration that cause the sensor response to be highly dynamic and to seldom reach a steady state. Therefore the discrimination of gases has to be performed on features extracted from the dynamics of the signal. The problem is further complicated by variations in temperature and humidity, physical variables to which metal oxide gas sensors are crossensitive. For these reasons the problem of discrimination of gases when an array of sensors is directly exposed to the environment is different from when the array of sensors is in a controlled chamber.i ii This thesis is a compilation of papers whose contributions are two folded. On one side new algorithms for discrimination of gases with an array of sensors directly exposed to the environment are presented. On the other side, innovative experimental setups are proposed. These experimental setups enable the collection of high quality data that allow a better insight in the problem of discrimination of gases with mobile robots equipped with an e-nose. The algorithmic contributions start with the design and validation of a gas discrimination algorithm for gas sensors array directly exposed to the environment. The algorithm is then further developed in order to be able to run online on a robot, thereby enabling t...

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Theoretical analysis of three bio-inspired plume tracking algorithms

Cited by 40 publications

References 26 publications

Using Chemical Sensors as “Noses” for Mobile Robots

Using Chemical Sensors as “Noses” for Mobile Robots

Bootstrapping bilinear models of Simple Vehicles

Gas Discrimination for Mobile Robots

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