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Indoor odour source localisation using robot: Initial location and surge distance matter?

ROBOTICS AND AUTONOMOUS SYSTEMS 2013年第6期61卷 637-647页

作者： Lu, Tien-Fu Univ Adelaide Dept Mech Adelaide SA 5005 Australia

Learning from insects and animals to enable an autonomous robot to detect chemical emissions caused by fire, toxic gas leakage and explosive at their early stages, and localise their sources swiftly can avoid risking human health and even save lives. This paper presents a series of investigations aimed to find answers for two important questions, one is "Are there advantageous locations when releasing a robot for speedier chemical source localisation with no prior knowledge about the environment as well as the possible location of the source?" The other question is similar but focusing on whether a different surge distance makes any noticeable differences. To find the answers, a simulated autonomous robot and an indoor office-like environment which contains an odour/gas source emitting varying chemical concentration levels as well as constantly varied wind speeds and directions, were adopted. (C) 2013 Elsevier B.V. All rights reserved.

关键词： odour source localisation Initial location Surge distance Robot Plume tracing

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Chemical plume tracing and odour source localisation by autonomous vehicles

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JOURNAL OF NAVIGATION 2007年第2期60卷 173-190页

作者： Naeem, W. Sutton, R. Chudley, J. Univ Plymouth Plymouth PL4 8AA Devon England

Autonomous vehicles with an ability to trace chemical plumes can be instrumental in tasks such as detection of unexploded ordnance, search for undersea wreckage and environmental monitoring. As a consequence, use of autonomous vehicles to perform chemical plume tracing has received an increasing interest from the research community in recent years. Owing to the diversity of applications and ambient fluid environment of the plumes, there are numerous plume tracing strategies and approaches. This paper reviews two main approaches and a number of strategies that have been successfully implemented to track air or water borne plumes in order to locate odour sources using autonomous vehicles. The first strategy considered is the biomimetic approach that offers excellent models for the development of robotic systems. Strategies inspired by lobsters and bacterium are the main focus in this study. The second scheme considers parallelization of the search procedure by employing a multi-robot approach. This approach has the advantage of utilising a group of smaller and simpler communicating robots which are capable of performing a collaborative search of the plume.

关键词： chemical plume tracing odour source localisation guidance autonomous vehicle

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A performance comparison of bio-inspired behaviours for odour source localisation 19

A performance comparison of bio-inspired behaviours for odou...

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19th IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

作者： Macedo, Joao Marques, Lino Costa, Ernesto Univ Coimbra Ctr Informat & Syst Inst Syst & Robot Coimbra Portugal Univ Coimbra Inst Syst & Robot Coimbra Portugal Univ Coimbra Ctr Informat & Syst Coimbra Portugal

ISBN: (纸本)9781728135588

Detecting and locating odour sources with mobile robots is hard, yet an interesting problem for many real world applications. In nature, this problem is daily and successfully addressed as a way to survive. This success motivated researchers to adapt the observed biological search strategies for robots. Each of these strategies is meant to operate under specific environmental conditions and, despite being inherently different, they can be decomposed into a small set of behaviours. The present paper compares the performance of those behaviours in finding and tracking odour plumes to their sources, under diverse environmental conditions. The experimental results show that the performance of each behaviour is highly dependent on its parameters, as well as on the involving environmental conditions and thus, the behaviour employed must be carefully selected. The resulting knowledge may be used by the community for producing better performing strategies, either by hand-designing them or through learning methods.

关键词： Mobile Robot Olfaction odour source localisation Bio-Inspired Strategies

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A Comparative Study of Bio-Inspired odour source localisation Strategies from the State-Action Perspective

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SENSORS 2019年第10期19卷 2231.-2231.页

作者： Macedo, Joao Marques, Lino Costa, Ernesto Univ Coimbra Inst Syst & Robot P-3030290 Coimbra Portugal Univ Coimbra Ctr Informat & Syst P-3030290 Coimbra Portugal

Locating odour sources with robots is an interesting problem with many important real-world applications. In the past years, the robotics community has adapted several bio-inspired strategies to search for odour sources in a variety of environments. This work studies and compares some of the most common strategies from a behavioural perspective with the aim of knowing: (1) how different are the behaviours exhibited by the strategies for the same perceptual state;and (2) which are the most consensual actions for each perceptual state in each environment. The first step of this analysis consists of clustering the perceptual states, and building histograms of the actions taken for each cluster. In case of (1), a histogram is made for each strategy separately, whereas for (2), a single histogram containing the actions of all strategies is produced for each cluster of states. Finally, statistical hypotheses tests are used to find the statistically significant differences between the behaviours of the strategies in each state. The data used for performing this study was gathered from a purpose-built simulator which accurately simulates the real-world phenomena of odour dispersion and air flow, whilst being sufficiently fast to be employed in learning and evolutionary robotics experiments. This paper also proposes an xml-inspired structure for the generated datasets that are used to store the perceptual information of the robots over the course of the simulations. These datasets may be used in learning experiments to estimate the quality of a candidate solution or for measuring its novelty.

关键词： odour source localisation mobile robot olfaction bio-inspired strategies

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Assessing Infotaxis Sensitivity to Model Quality Through Evolutionary Computation 6th

Assessing Infotaxis Sensitivity to Model Quality Through Evo...

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6th Iberian Robotics Conference (Robot)

作者： Macedo, Joao Marques, Lino Costa, Ernesto Univ Coimbra Ctr Informat & Syst Coimbra Portugal Univ Coimbra Inst Syst & Robot P-3030290 Coimbra Portugal

ISBN: (纸本)9783031586750;9783031586767

Locating odour sources with mobile robots is a difficult task that can be applied to locating the sources of pollutants, concealed explosives or victims in disaster scenarios. The existing approaches for locating odour sources can be divided between those that simply seek to reach the chemical source, and those that use gas dispersion models to estimate its location. One of the most popular source estimation approaches is Infotaxis, which has been shown to have great sensitivity to the parameters of its gas distribution model. In this paper, we compare two evolutionary approaches for automatically selecting the values for these parameters along with a Genetic Programming approach for evolving human-readable source-seeking strategies. The comparisons are carried out in three simulated environments with different chemical plumes and the results show that the parameters that best fit the environment do not always lead to the highest performance. Also, depending on the scenario, the tree-based search strategies are able to perform equivalently to Infotaxis, at a lesser computational cost.

关键词： odour source localisation Evolutionary Robotics Infotaxis Genetic Algorithms

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Hybridizing Bio-Inspired Strategies with Infotaxis through Genetic Programming

Hybridizing Bio-Inspired Strategies with Infotaxis through G...

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Genetic and Evolutionary Computation Conference (GECCO)

作者： Macedo, Joao Marques, Lino Costa, Ernesto Univ Coimbra Coimbra Portugal

ISBN: (纸本)9781450392372

Locating odour sources with mobile robots is a difficult task with many applications. Over the years, researchers have devised bio-inspired and cognitive methods to enable mobile robots to fulfil this task. Cognitive approaches are effective in large spaces, but computationally heavy. On the other hand, bio-inspired ones are lightweight, but they are only effective in the presence of frequent stimuli. One of the most popular cognitive approaches is Infotaxis, which iteratively computes a probability map of the source location. Another strand of work uses Genetic Programming to produce complete search strategies from bio-inspired behaviours. This work combines the two approaches by allowing Genetic Programming to evolve search strategies that include infotactic and bio-inspired behaviours. The proposed method is tested in a set of environments with distinct airflow and chemical dispersion patterns. Its performance is compared to that of evolved strategies without infotactic behaviours and to the standard infotaxis approach. The statistically validated results show that the proposed method produces search strategies that have significantly higher success rates, whilst being faster than those produced by any of the original approaches. Moreover, the best evolved strategies are analysed, providing insight into when infotaxis is more beneficial.

关键词： Evolutionary Robotics Genetic Programming odour source localisation Robotics Infotaxis

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Studying Exploitation and Exploration Trade-Off of Cognitive odour-Guided Search 6th

Studying Exploitation and Exploration Trade-Off of Cognitive...

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6th Iberian Robotics Conference (Robot)

作者： Magalhaes, Hugo Baptista, Rui Marques, Lino Univ Coimbra Inst Syst & Robot P-3030790 Coimbra Portugal

ISBN: (纸本)9783031586750;9783031586767

Cognitive search strategies are highly suitable for odour source localisation (OSL) under turbulent flow conditions where continuous cues are not always available. While reliable, these methods have a known tendency to shift the weight of the search towards exploration, which increases the time and distance required to locate the source. Balancing the trade-off between exploration and exploitation (EE) is crucial since it can directly influence the efficiency and reliability of the mission. However, its understanding from a motion decision perspective still remains unclear with most conclusions being drawn from visual interpretation of the search trajectories or from results of performance metrics. This work aims to study the EE trade-off of cognitive OSL actions by identifying movement patterns and quantifying their values for multiple metrics associated with the decision. A large number of experiments were performed under realistic simulated environments, with the results showing the emergence of multiple well-defined movement patterns and EE tendencies that remain identical across different scenarios.

关键词： odour source localisation Information-theoretic Field robotics

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Locating odour sources with Geometric Syntactic Genetic Programming 1

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23rd European International Conference on the Applications of Evolutionary Computation (EvoApplications) Held as Part of EvoStar Conference

作者： Macedo, Joao Marques, Lino Costa, Ernesto Univ Coimbra Dept Elect & Comp Engn ISR P-3030290 Coimbra Portugal Univ Coimbra Dept Informat Engn CISUC P-3030290 Coimbra Portugal

ISBN: (数字)9783030437220

ISBN: (纸本)9783030437213;9783030437220

Using robots to locate odour sources is an interesting problem with important applications. Many researchers have drawn inspiration from nature to produce robotic methods, whilst others have attempted to automatically create search strategies with Artificial Intelligence techniques. This paper extends Geometric Syntactic Genetic Programming and applies it to automatically produce robotic controllers in the form of behaviour trees. The modification proposed enables Geometric Syntactic Genetic Programming to evolve trees containing multiple symbols per node. The behaviour trees produced by this algorithm are compared to those evolved by a standard Genetic Programming algorithm and to two bio-inspired strategies from the literature, both in simulation and in the real world. The statistically validated results show that the Geometric Syntactic Genetic Programming algorithm is able to produce behaviour trees that outperform the bio-inspired strategies, while being significantly smaller than those evolved by the standard Genetic Programming algorithm. Moreover, that reduction in size does not imply statistically significant differences in the performance of the strategies.

关键词： Evolutionary Robotics odour source localisation Genetic Programming Geometric operators

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