| 1. |
- Lilienthal, Achim J., 1970-, et al.
(författare)
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Gas source declaration with a mobile robot
- 2004
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Ingår i: 2004 IEEE International Conference on Robotics and Automation. - New York, USA : IEEE. - 0780382323 ; , s. 1430-1435
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Konferensbidrag (refereegranskat)abstract
- As a sub-task of the general gas source localisation problem, gas source declaration is the process of determining the certainty that a source is in the immediate vicinity. Due to the turbulent character of gas transport in a natural indoor environment, it is not sufficient to search for instantaneous concentration maxima, in order to solve this task. Therefore, this paper introduces a method to classify whether an object is a gas source or not from a series of concentration measurements, recorded while the robot performs a rotation manoeuvre in front of a possible source. For three different gas source positions, a total of 288 declaration experiments were carried out at different robot-to-source distances. Based on these readings, two machine learning techniques (ANN, SVM) were evaluated in terms of their classification performance. With learning parameters that were optimised by grid search, a maximal hit rate of approximately 87.5% could be obtained using a support vector machine
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| 2. |
- Lilienthal, Achim J., 1970-, et al.
(författare)
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Detection and Localization of an Odour Source by an autonomous mobile Robot
- 2002
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Ingår i: Robotik 2002. - Dusseldorf, Germany : V D I-V D E - VERLAG GMBH. - 3180916796 ; , s. 689-694
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Konferensbidrag (refereegranskat)abstract
- This paper presents studies concerning the use of an electronic nose on an autonomous mobile robot. In particular experiments were introduced in which a mobile robot generates two dimensional concentration maps of a known target gas in an unventilated room. It was shown that these concentration maps are clearly related to the position of the odour source. Moreover our results show that if accurate localization of the odour source itself is desired one has to consider weak air currents which usually occur even in closed unventilated rooms (often caused by convection).
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| 3. |
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| 4. |
- Lilienthal, Achim J., 1970-, et al.
(författare)
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Experiences using gas sensors on an autonomous mobile robot
- 2001
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Ingår i: Proceedings of EUROBOT 2001, 4th European workshop on advanced mobile robots. ; , s. 1-8
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Konferensbidrag (refereegranskat)abstract
- This paper reports on experiences concerning the deployment of gas sensors on an autonomous mobile robot. It particularly addresses the suitability of the developed system to localize a distant odour source. First experiments were undertaken in which the robot was ordered to move along different weakly ventilated corridors, while keeping track of its center (framing a '1D' scenario). The measured sensor values show evident peaks that roughly indicate the location of the odour source, if the robot moves with a speed not too low. In this case the system proved to be well suited to detect even weak odour sources. Otherwise the observed course of the received values show many peaks hardly correlated with the location of the odour source. Several investigations were performed to clear up this behaviour but it is still not possible to make concluding statements about the reasons. Finally the setup to perform experiments in a '2D' scenario is described and concerning results of first investigations are presented. It was shown that the utilized system is also capable of detecting a distant odour source in a 2D environment and that the somewhat harder localization task has to account for some weak airflow even in closed, unventilated rooms.
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| 5. |
- Lilienthal, Achim J., 1970-, et al.
(författare)
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Gas source tracing with a mobile robot using an adapted moth strategy
- 2003
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Ingår i: Autonome mobile systeme 2003. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783540201427 - 9783642189869 ; , s. 150-160
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Konferensbidrag (refereegranskat)abstract
- As a sub-task of the general gas source localisation problem, gas source tracing is supposed to guide a gas-sensitive mobile system towards a source by using the cues determined from the gas distribution sensed along a driven path. This paper reports on an investigation of a biologically inspired gas source tracing strategy. Similar to the behaviour of the silkworm moth Bombyx mori, the implemented behaviour consists of a fixed motion pattern that realises a local search, and a mechanism that (re-)starts this motion pattern if an increased gas concentration is sensed. While the moth uses the local airflow direction to orient the motion pattern, this is not possible for a mobile robot due to the detection limits of currently available anemometers. Thus, an alternative method was implemented that uses an asymmetric motion pattern, which is biased towards the side where higher gas sensor readings were obtained. The adaptated strategy was implemented and tested on an experimental platform. This paper describes the strategy and evaluates its performance in terms of the ability to drive the robot towards a gas source and to keep it within close proximity of the source
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| 6. |
- Lilienthal, Achim J., 1970-, et al.
(författare)
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Learning to detect proximity to a gas source with a mobile robot
- 2004
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Ingår i: 2004 IEEE/RSJ international conference on intelligent robots and systems, 2004 (IROS 2004). - : Institute of Electrical and Electronics Engineers (IEEE). - 0780384636 ; , s. 1444-1449
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Konferensbidrag (refereegranskat)abstract
- As a sub-task of the general gas source localisation problem, gas source declaration is the process of determining the certainty that a source is in the immediate vicinity. Due to the turbulent character of gas transport in a natural indoor environment, it is not sufficient to search for instantaneous concentration maxima, in order to solve this task. Therefore, this paper introduces a method to classify whether an object is a gas source from a series of concentration measurements, recorded while the robot performs a rotation manoeuvre in front of a possible source. For three different gas source positions, a total of 1056 declaration experiments were carried out at different robot-to-source distances. Based on these readings, support vector machines (SVM) with optimised learning parameters were trained and the cross-validation classification performance was evaluated. The results demonstrate the feasibility of the approach to detect proximity to a gas source using only gas sensors. The paper presents also an analysis of the classification rate depending on the desired declaration accuracy, and a comparison with the classification rate that can be achieved by selecting an optimal threshold value regarding the mean sensor signal.
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| 7. |
- Lilienthal, Achim J., 1970-, et al.
(författare)
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Model-based shape analysis of gas concentration grinmaps for improved gas source localisation
- 2005
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Ingår i: Proceedings of the 2005 IEEE International Conference on Robotics and Automation. - : Institute of Electrical and Electronics Engineers (IEEE). - 078038914X ; , s. 3564-3569
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Konferensbidrag (refereegranskat)abstract
- This work addresses the capability to use concentration gridmaps to locate a static gas source. In previous works it was found that depending on the shape of the mapped gas distribution (corresponding to different airflow conditions) the gas source location can be sometimes approximated with high accuracy by the maximum in the concentration map while this is not possible in other cases. This paper introduces a method to distinguish both cases by analysing the shape of the obtained concentration map in terms of a model of the time-averaged gas distribution known from physics. The parameters of the model that approximates the concentration map most closely are determined by nonlinear least squares fitting using evolution strategies (ES). The best fit also provides a better estimate of the gas source position in situations where the concentration maximum estimate fails. Different methods to select the most truthful estimate are introduced in this work and a comparison regarding their accuracy is presented, based on a total of 34h of concentration mapping experiments.
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| 8. |
- Lilienthal, Achim J., 1970-, et al.
(författare)
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Sensing odour sources in indoor environments without a constant airflow by a mobile robot
- 2001
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Ingår i: Proceedings 2001 ICRA. - : IEEE. - 0780365763 ; , s. 4005-4010
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Konferensbidrag (refereegranskat)abstract
- This paper describes the assembly of a mobile odour sensing system and investigates its practical operation in an indoor environment without a constant airflow. Lacking a constant airflow leads to a problem which cannot be neglected in real world applications. The response of the metal oxide gas sensors used is dominated by air turbulence rather than concentration differences. We show that this problem can be overcome by driving the robot with a constant speed, thus adding an extra constant airflow relative to the gas sensors location. If the robot's speed is not too low the system described proved to be well suited to detect even weak odour sources. Since driving with constant speed is an indispensable condition to perform the basic tasks of a mobile odour sensing system, a new localization strategy is proposed, which takes this into account.
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| 9. |
- Tamimi, Hashem, et al.
(författare)
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Localization of mobile robots with omnidirectional vision using Particle Filter and iterative SIFT
- 2006
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Ingår i: Robotics and Autonomous Systems. - : Elsevier BV. - 0921-8890 .- 1872-793X. ; 54:9, s. 758-765
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Tidskriftsartikel (refereegranskat)abstract
- The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot localization. Still, the number of features extracted with this approach is immense, especially when dealing with omnidirectional vision. In this work, we propose a new approach that reduces the number of features generated by SIFT as well as their extraction and matching time. With the help of a Particle Filter, we demonstrate that we can still localize the mobile robot accurately with a lower number of features
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| 10. |
- Tamimi, Hashem, et al.
(författare)
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Localization of mobile robots with omnidirectional vision using particle filter and iterative SIFT
- 2005
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Konferensbidrag (refereegranskat)abstract
- The Scale Invariant Feature Transform, SIFT, has been successfully applied to robot localization. Still, the number of features extracted with this approach is immense, especially when dealing with omnidirectional vision. In this work, we propose a new approach that reduces the number of features generated by SIFT as well as their extraction and matching time. With the help of a particle filter, we demonstrate that we can still localize the mobile robot accurately with a lower number of features
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