A Graph-Based Formation Algorithm for Odor Plume Tracing

Soares, Jorge M.; Aguiar, A. Pedro; Pascoal, António; Martinoli, Alcherio

doi:10.1007/978-4-431-55879-8_18

Cited by 8 publications

(8 citation statements)

References 27 publications

(30 reference statements)

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“…Unfortunately, the disturbance effect of drones on sensor measurements and their short endurance have severely limited their application. In what concerns ground operations, most robotic platforms are wheeled and in particular nonholonomic unicycle-modeled robots (two wheel differential drive with additional passive wheels) are popular, due to their simple design and superior maneuverability [10 • ], [11,12,13,14], [15 • ]. Among all types of vehicles, marine robots are probably the most challenging to build and operate in the adverse conditions imposed by the water medium.…”

Section: Robotic Platforms and Field Experimentsmentioning

confidence: 99%

“…Notice that experimental results such as odor tracing in a wind tunnel [10 • ], [11,12,13,14], [15 • ], underground gas leakage tracing in a and pool [7], and source tracing in a controlled water reservoir [20,23], were all carried out in controlled environments. On the other Figure 1 (adapted from [29]): Example of chemotaxis of three agents using a leader-follower approach.…”

Section: Robotic Platforms and Field Experimentsmentioning

confidence: 99%

“…Recently, in [10 • ], [11] a formation control scheme based on ranges from other agents was employed for odor source localization and tracing in a two dimensional (2D) wind tunnel via Laplacian feedback formation control [43] of multiple cooperative robots in a variety of formations (see figure 2). Source localization was done by plume centering of the formation based on odor measurements obtained from all the robots in the formation.…”

Section: Wind Detection (Anemotaxis)mentioning

confidence: 99%

See 2 more Smart Citations

Environmental monitoring using autonomous vehicles: a survey of recent searching techniques

Bayat

Crasta

Crespi

et al. 2017

Current Opinion in Biotechnology

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128

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Autonomous vehicles are becoming an essential tool in a wide range of environmental applications that include ambient data acquisition, remote sensing, and mapping of the spatial extent of pollutant spills. Among these applications, pollution source localization has drawn increasing interest due to its scientific and commercial interest and the emergence of a new breed of robotic vehicles capable of performing demanding tasks in harsh environments without human supervision. In this task, the aim is to find the location of a region that is the source of a given substance of interest (e.g. a chemical pollutant at sea or a gas leakage in air) using a group of cooperative autonomous vehicles. Motivated by fast paced advances in this challenging area, this paper surveys recent advances in searching techniques that are at the core of environmental monitoring strategies using autonomous vehicles.

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Section: Robotic Platforms and Field Experimentsmentioning

confidence: 99%

Section: Robotic Platforms and Field Experimentsmentioning

confidence: 99%

Section: Wind Detection (Anemotaxis)mentioning

confidence: 99%

See 1 more Smart Citation

Environmental monitoring using autonomous vehicles: a survey of recent searching techniques

Bayat

Crasta

Crespi

et al. 2017

Current Opinion in Biotechnology

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128

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“…At each time step, the position of a filament is updated according to a uniform wind field and a stochastic process consisting of a vector of three independent Gaussian random variables. More details of the odor dispersion simulation in Webots are provided in [32].…”

Section: ) Setupmentioning

confidence: 99%

“…We approach the problem by adapting our previously proposed graph-based Laplacian formation method [20], [32], [33] to a 3-D system consisting of ground and aerial robots. The 2-D version of our method works on two basic principles: i) under stable wind conditions, the wind direction provides a strong hint as to the relative position of the source; and ii) having multiple robots distributed in the environment provides us with enough data to allow a computationally simple algorithm to track a plume in spite of its patchiness.…”

Section: Introductionmentioning

confidence: 99%

Towards 3-D distributed odor source localization: An extended graph-based formation control algorithm for plume tracking

Soares¹,

Marjovi²,

Giezendanner³

et al. 2016

2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-The large number of potential applications for robotic odor source localization has motivated the development of a variety of plume tracking algorithms, the majority of which work in restricted two-dimensional scenarios. In this paper, we introduce a distributed algorithm for 3-D plume tracking using a system of ground and aerial robots in formation. We propose an algorithm that takes advantage of spatially distributed measurements to track the plume in 3-D and lead the robots to the source by integrating three behaviors -upwind movement, plume centering, and Laplacian feedback formation control. We evaluate this strategy in simulation and with real robots in a wind tunnel. For a source close to the ground, results show that a team of robots running our algorithm reaches the source with low lateral error while also tracing the horizontal and vertical plume shape.

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Middleware for Multi-robot Systems

Sahni

Cao

Jiang

2019

Mission-Oriented Sensor Networks and Systems: Art and Science

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Recent advances in robotics technology have made it viable to assign complex tasks to large numbers of inexpensive robots. The robots as an ensemble form into a multi-robot system (MRS), which can be utilized for many applications where a single robot is not efficient or feasible. MRS can be used for a wide variety of application domains such as military, agriculture, smart home, disaster relief, etc. It offers higher scalability, reliability, and efficiency as compared to single robot system. However, it is non-trivial to develop and deploy MRS applications due to many challenging issues such as distributed computation, collaboration, coordination, and real-time integration of robotic modules and services. To make the development of multi-robot applications easier, researchers have proposed various middleware architectures to provide programming abstractions that help in managing the complexity and heterogeneity of hardware and applications. With the help of middleware, an application developer can concentrate on the high-level logic of applications instead of worrying about low-level hardware and network details. In this chapter, we survey state of the art in both distributed MRS and middleware being used for developing their applications. We provide a taxonomy that can be used to classify the MRS middleware and analyze existing middleware functionalities and features. Our work will help researchers and developers in the systematic understanding of middleware for MRS and in selecting or developing the appropriate middleware based on the application requirements.

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A Graph-Based Formation Algorithm for Odor Plume Tracing

Cited by 8 publications

References 27 publications

Environmental monitoring using autonomous vehicles: a survey of recent searching techniques

Environmental monitoring using autonomous vehicles: a survey of recent searching techniques

Towards 3-D distributed odor source localization: An extended graph-based formation control algorithm for plume tracking

Middleware for Multi-robot Systems

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