A comparison of reactive robot chemotaxis algorithms

Russell, R. A.; Bab–Hadiashar, Alireza; Shepherd, Rod L.; Wallace, Gordon G.

doi:10.1016/s0921-8890(03)00120-9

Cited by 242 publications

(158 citation statements)

References 13 publications

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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%

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

Bayat

Crasta

Crespi

et al. 2017

Current Opinion in Biotechnology

145

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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%

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

Bayat

Crasta

Crespi

et al. 2017

Current Opinion in Biotechnology

145

View full text Add to dashboard Cite

show abstract

“…This means that if the direction of the airflow changes over time the direction of the x and y axes in coordinate system of the robot also changes and the robots always align their desired topology with the state of the airflow. Moreover, based on (10) and (11), the distance between the neighboring robots dynamically modifies if the airflow speed changes.…”

Section: The Total Forcementioning

confidence: 99%

“…Finding an odor plume, i.e., searching the environment randomly or systematically in order to find odor clues is the final goal of this study. This is the first phase in search for odor sources [11]. The second phase is plume tracking, that is, following the plume towards the source, and the final step is source declaration, that is, accurately localizing the source [12].…”

Section: Introductionmentioning

confidence: 99%

Optimal Swarm Formation for Odor Plume Finding

Marjovi

Marques

2014

IEEE Trans. Cybern.

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Abstract-This paper presents an analytical approach to the problem of odor plume finding by a network of swarm robotic gas sensors and finds an optimal configuration for them, given a set of assumptions. Considering cross-wind movement for the swarm, we found that the best spatial formation of robots in finding odor plumes is diagonal line configuration with equal distance between each pair of neighboring robots. We show that the distance between neighboring pairs in the line topology depends mainly on the wind speed and the environmental conditions, whereas, the number of robots and the swarm's crosswind movement distance do not show significant impact on optimal configurations. These solutions were analyzed and verified by simulations and experimentally validated in a reduced scale realistic environment using a set of mobile robots.

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“…Researchers have developed methods that employ combinations and variations of plume acquisition [8,9] and plume upwind following [5,8,10] using reactive control algorithms (a comparison of these methods is in [11]). Most of these approaches are inspired by very simple creatures like moths [3], glowworms [12], etc, therefore they are mostly low-level algorithms making the robot react to the environmental changes based on some defined rules.…”

Section: Multi-robot Olfactory Searchingmentioning

confidence: 99%

Multi-robot olfactory search in structured environments

Marjovi

Marques

2011

Robotics and Autonomous Systems

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This paper presents a cooperative distributed approach for searching odor sources in unknown structured environments with multiple mobile robots . While searching and exploring the environment, the robots independently generate on-line local topological maps and by sharing them with each other they construct a global map. The proposed method is a decentralized frontier based algorithm enhanced by a cost/utility evaluation function that considers the odor concentration and airflow at each frontier. Therefore, frontiers with higher probability of containing an odor source will be searched and explored first. The method also improves path planning of the robots for exploration process by presenting a priority policy. Since there is no global positioning system and each robot has its own coordinate reference system for its localization, this paper uses topological graph matching techniques for map merging. The proposed method was tested in both simulation and real world environments with different number of robots and different scenarios. The search time, exploration time, complexity of the environment and number of double-visited map nodes were investigated in the tests. The experimental results validate the functionality of the method in different configurations.

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A comparison of reactive robot chemotaxis algorithms

Cited by 242 publications

References 13 publications

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

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

Optimal Swarm Formation for Odor Plume Finding

Multi-robot olfactory search in structured environments

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