A 3-D bio-inspired odor source localization and its validation in realistic environmental conditions

Rahbar, Faezeh; Marjovi, Ali; Kibleur, Pierre; Martinoli, Alcherio

doi:10.1109/iros.2017.8206252

Cited by 25 publications

(29 citation statements)

References 25 publications

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“…To compare the performance of our algorithm with other methods, as mentioned in the introduction, there are not many previous works studying the problem in 3D, and among them, only our previous work in [16] (a moth-inspired algorithm) Table III. has comparable environmental conditions and experimental setup. Compared to [16], our new method has a better over-all success rate, especially at higher wind speeds (e.g., in setup E, the 3D infotaxis shows 100% success rate, whereas in [16] it was 70%). It is relatively slower in finding the source, due to the concentration sampling time at every step, but this difference is not very significant.…”

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Design and Performance Evaluation of an Infotaxis-Based Three-Dimensional Algorithm for Odor Source Localization

Julian

Marjovi

Rahbar

et al. 2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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In this paper we tackle the problem of finding the source of a gaseous leak with a robot in a three-dimensional (3-D) physical space. The proposed method extends the operational range of the probabilistic Infotaxis algorithm [1] into 3-D and makes multiple improvements in order to increase its performance in such settings. The method has been tested systematically through high-fidelity simulations and in a wind tunnel emulating realistic conditions. The impact of multiple algorithmic and environmental parameters has been studied in the experiments. The algorithm shows good performance in various environmental conditions, particularly in high wind speeds and different source release rates.

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Section: Resultsmentioning

confidence: 99%

“…In most cases, the methods are evaluated in simplified conditions, (e.g., [12] and [13]). Only a few have been carried out in realistic [14] or controlled environments (e.g., [15] and [16]), and all are based on simple gradient-based or bio-inspired algorithms. Recently a 3-D formation-based system has also been presented [6].…”

Section: Introductionmentioning

confidence: 99%

Design and Performance Evaluation of an Infotaxis-Based Three-Dimensional Algorithm for Odor Source Localization

Julian

Marjovi

Rahbar

et al. 2018

2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Self Cite

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“…Note that there have been several source localization experiments, rather than STE, that have been carried out (see [9], [42]). These methods did not estimate important parameters of the release, such as its strength, and the robots were generally initiated downwind of the source within the dispersion.…”

Section: Related Workmentioning

confidence: 99%

Information-Based Search for an Atmospheric Release Using a Mobile Robot: Algorithm and Experiments

Hutchinson

Liu

Chen

2019

IEEE Trans. Contr. Syst. Technol.

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Finding the location and strength of an unknown hazardous release is of paramount importance in emergency response and environmental monitoring; thus, it has been an active research area for several years known as source term estimation (STE). This paper presents a joint Bayesian estimation and planning algorithm to guide a mobile robot to collect informative measurements, allowing the source parameters to be estimated quickly and accurately. The estimation is performed recursively using Bayes' theorem, where uncertainties in the meteorological and dispersion parameters are considered and the intermittent readings from a low-cost gas sensor are addressed by a novel likelihood function. The planning strategy is designed to maximize the expected utility function based on the estimated information gain of the source parameters. Subsequently, this paper presents the first experimental result of such a system in turbulent, diffusive conditions, in which a ground robot equipped with the low-cost gas sensor responds to the hazardous source simulated by incense sticks. The experimental results demonstrate the effectiveness of the proposed estimation and search algorithm for STE based on the mobile robot and the low-cost sensor.

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“…Typical applications are Chemical Plume Tracing (CPT) [19], [22], source pollution tracking , as well in an atmospheric [8], [15] or underwater context [2], [22], and rescue missions [11]. However communications are much more constrained underwater than in the air, thus atmospheric methods can not be applied directly to the underwater world.…”

Section: Introductionmentioning

confidence: 99%

A Local Charged Particle Swarm Optimization to track an underwater mobile source

Coquet¹,

Aubry²,

Arnold³

et al. 2019

OCEANS 2019 - Marseille

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In this paper, a possible solution to track a mobile underwater source in a closed environment with N Autonomous Underwater Vehicles (AUV) in a swarm formation is adressed. The source tracking algorithm is defined as successful when the range between the source and the swarm is sufficiently low during a given duration, short enough to perform a specified action (for example a source localization). A source is defined as an entity that releases a scalar information affected by transport and diffusion in the environment. We use a generic time-varying information f (pi(t)), where pi at time t is the m-dimensional position of a tracker i and function f (.) is a function that represents sensor information. In this paper, we propose an innovative tracking method inspired by the Particle Swarm Optimization (PSO) algorithm that we call the Local Charged Particle Swarm Optimization (LCPSO). The proposed algorithm is adapted to range-dependant communication that characterizes the underwater context and includes flocking parameters. Comparison of the LCPSO against state of the art methods demonstrate the interest of our approach in an underwater scenario.

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A 3-D bio-inspired odor source localization and its validation in realistic environmental conditions

Cited by 25 publications

References 25 publications

Design and Performance Evaluation of an Infotaxis-Based Three-Dimensional Algorithm for Odor Source Localization

Design and Performance Evaluation of an Infotaxis-Based Three-Dimensional Algorithm for Odor Source Localization

Information-Based Search for an Atmospheric Release Using a Mobile Robot: Algorithm and Experiments

A Local Charged Particle Swarm Optimization to track an underwater mobile source

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