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  • 1.
    Aleotti, Jacopo
    et al.
    Örebro universitet, Institutionen för teknik.
    Skoglund, Alexander
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Position teaching of a robot arm by demonstration with a wearable input device2004Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper describes the first prototype of a "Programming by demonstration" (PbD) system for position teaching of a robot manipulator. A new approach for enabling PbD using supervised learning is presented, by connecting a wearable input device for sensing human arm movements to the software controller of a robot arm. The method does not require analytical modelling of either the human arm or robot, and can be customised for different users and robots. Initial experiments on some simple movements tasks are presented.

  • 2.
    Andreasson, Henrik
    et al.
    Örebro universitet, Institutionen för teknik.
    Treptow, André
    University of Tübingen.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Localization for mobile robots using panoramic vision, local features and particle filter2005Ingår i: Proceedings of the 2005 IEEE International Converence on Robotics and Automation: ICRA - 2005, 2005, s. 3348-3353Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present a vision-based approach to self-localization that uses a novel scheme to integrate featurebased matching of panoramic images with Monte Carlo localization. A specially modified version of Lowe’s SIFT algorithm is used to match features extracted from local interest points in the image, rather than using global features calculated from the whole image. Experiments conducted in a large, populated indoor environment (up to 5 persons visible) over a period of several months demonstrate the robustness of the approach, including kidnapping and occlusion of up to 90% of the robot’s field of view.

  • 3.
    Andreasson, Henrik
    et al.
    Örebro universitet, Institutionen för teknik.
    Treptow, André
    University of Tübingen.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Self-localization in non-stationary environments using omni-directional vision2007Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 55, nr 7, s. 541-551Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents an image-based approach for localization in non-static environments using local feature descriptors, and its experimental evaluation in a large, dynamic, populated environment where the time interval between the collected data sets is up to two months. By using local features together with panoramic images, robustness and invariance to large changes in the environment can be handled. Results from global place recognition with no evidence accumulation and a Monte Carlo localization method are shown. To test the approach even further, experiments were conducted with up to 90% virtual occlusion in addition to the dynamic changes in the environment

  • 4.
    Cielniak, Grzegorz
    et al.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    People recognition by mobile robots2004Ingår i: Journal of Intelligent & Fuzzy Systems, ISSN 1064-1246, E-ISSN 1875-8967, Vol. 15, nr 1, s. 21-27Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of detecting and identifying persons with a mobile robot, by sensory fusion of thermal and colour vision information. In the proposed system, people are first detected with a thermal camera, using image analysis techniques to segment the persons in the thermal images. This information is then used to segment the corresponding regions of the colour images, using an affine transformation to solve the image correspondence between the two cameras. After segmentation, the region of the image containing a person is further divided into regions corresponding to the person's head, torso and legs. Temperature and colour features are then extracted from each region for input to a pattern recognition system. Three alternative classfication methods were investigated in experiments with a moving mobile robot and moving persons in an office environment. The best identification performance was obtained with a dynamic recognition method based on a Bayes classifier, which takes into account evidence accumulated in a sequence of images.

  • 5.
    Cielniak, Grzegorz
    et al.
    Department of Computing and Informatics, University of Lincoln, Lincoln, United Kingdom.
    Duckett, Tom
    Department of Computing and Informatics, University of Lincoln, Lincoln, United Kingdom.
    Lilienthal, Achim J.
    Örebro universitet, Institutionen för teknik.
    Improved data association and occlusion handling for vision-based people tracking by mobile robots2007Ingår i: 2007 IEEE/RSJ international conference on intelligent robots and systems, New York, NY, USA: IEEE, 2007, s. 3436-3441Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents an approach for tracking multiple persons using a combination of colour and thermal vision sensors on a mobile robot. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is then incorporated into the tracker.

  • 6.
    Cielniak, Grzegorz
    et al.
    Örebro universitet, Institutionen för teknik.
    Miladinovic, Mihajlo
    Dept. of Technology, AASS, Örebro University, Örebro, Sweden.
    Hammarin, Daniel
    Dept. of Technology, AASS, Örebro University, Örebro, Sweden.
    Göransson, Linus
    Dept. of Technology, AASS, Örebro University, Örebro, Sweden.
    Lilienthal, Achim J.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Appearance-based tracking of persons with an omnidirectional vision sensor2003Ingår i: IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, IEEE, 2003, Vol. 7, artikel-id 4624346Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of tracking a moving person with a single, omnidirectional camera. An appearance-based tracking system is described which uses a self-acquired appearance model and a Kalman filter to estimate the position of the person. Features corresponding to ``depth cues'' are first extracted from the panoramic images, then an artificial neural network is trained to estimate the distance of the person from the camera. The estimates are combined using a discrete Kalman filter to track the position of the person over time. The ground truth information required for training the neural network and the experimental analysis was obtained from another vision system, which uses multiple webcams and triangulation to calculate the true position of the person. Experimental results show that the tracking system is accurate and reliable, and that its performance can be further improved by learning multiple, person-specific appearance models

  • 7.
    Cielniak, Grzegorz
    et al.
    Örebro universitet, Institutionen för teknik.
    Treptow, André
    University of Tübingen.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Quantitative performance evaluation of a people tracking system on a mobile robot2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    Future service robots will need to keep track of the persons in their environment. A number of people tracking systems have been developed for mobile robots, but it is currently impossible to make objective comparisons of their performance. This paper presents a comprehensive, quantitative evaluation of a state-of-the-art people tracking system for a mobile robot in an office environment, for both single and multiple persons.

  • 8.
    Duckett, Tom
    et al.
    Örebro universitet, Institutionen för teknik.
    Axelsson, Mikael
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för teknik.
    Learning to locate an odour source with a mobile robot2001Ingår i: IEEE international conference on robotics and automation: ICRA 2001, 2001, s. 4017-4022Konferensbidrag (Refereegranskat)
    Abstract [en]

    We address the problem of enabling a mobile robot to locate a stationary odour source using an electronic nose constructed from gas sensors. On the hardware side, we use a stereo nose architecture consisting of two parallel chambers, each containing an identical set of sensors. On the software side, we use a recurrent artificial neural network to learn the direction to a stationary source from a time series of sensor readings. This contrasts with previous approaches, that rely on the existence of a model of the sensor's dynamics. The complete system is able to orient and turn towards the source. An experimental validation was carried out to evaluate the performance of the system.

  • 9.
    Duckett, Tom
    et al.
    Örebro universitet, Institutionen för teknik.
    Marsland, Stephen
    University of Manchester.
    Shapiro, Jonathan
    University of Manchester.
    Fast, on-line learning of globally consistent maps2002Ingår i: Autonomous Robots, ISSN 0929-5593, E-ISSN 1573-7527, Vol. 12, nr 3, s. 287-300Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot be used to assign accurate global position information to a map because of cumulative drift errors. This paper introduces a fast, on-line algorithm for learning geometrically consistent maps using only local metric information. The algorithm works by using a relaxation technique to minimise an energy function over many small steps. The approach differs from previous work in that it is computationally cheap, easy to implement and is proven to converge to a globally optimal solution. Experiments are presented in which large, complex environments were successfully mapped by a real robot.

  • 10.
    Duckett, Tom
    et al.
    Örebro universitet, Institutionen för teknik.
    Nehmzow, Ulrich
    University of Manchester.
    Mobile robot self-localisation using occupancy histograms and a mixture of Gaussian location hypotheses2001Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 34, nr 2-3, s. 117-129Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The topic of mobile robot self-localisation is often divided into the sub-problems of global localisation and position tracking. Both are now well understood individually, but few mobile robots can deal simultaneously with the two problems in large, complex environments. In this paper, we present a unified approach to global localisation and position tracking which is based on a topological map augmented with metric information. This method combines a new scan matching technique, using histograms extracted from local occupancy grids, with an efficient algorithm for tracking multiple location hypotheses over time. The method was validated with experiments in a series of real world environments, including its integration into a complete navigating robot. The results show that the robot can localise itself reliably in large, indoor environments using minimal computational resources

  • 11.
    Duckett, Tom
    et al.
    Örebro universitet, Institutionen för teknik.
    Saffiotti, Alessandro
    Örebro universitet, Institutionen för teknik.
    Building globally consistent gridmaps from topologies2000Ingår i: Proceedings of the 6th international symposium on robot control: IFAC - (SYROCO), 2000, s. 357-361Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of recovering metric consistency in a global gridmap for mobile robot navigation. Gridmaps can only be updated consistently using exact estimates of the robot position, a requirement which is very hard to fulfil in real world environments because the same sensor data must be used for both map building and self-localisation. To overcome this problem, we use a hierarchy of robot maps which integrates topological and grid-based representations. The consistency problem is solved at the topological level, by applying a relaxation technique to generate coordinates for the places in the robot's map. Consequently, the robot is able to recover a globally consistent gridmap without requiring accurate sensors or high computational costs. Experiments on a Nomad 200 robot are presented which demonstrate the efficacy of our approach.

  • 12.
    Frese, Udo
    et al.
    University of Bremen.
    Larsson, Per
    NamaTec AB.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    A multilevel relaxation algorithm for simultaneous localisation and mapping2005Ingår i: IEEE Transactions on robotics, ISSN 1552-3098, E-ISSN 1941-0468, Vol. 21, nr 2, s. 196-207Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of simultaneous localisation and mapping (SLAM) by a mobile robot. An incremental SLAM algorithm is introduced that is derived from multigrid methods used for solving partial differential equations. The approach improves on the performance of previous relaxation methods for robot mapping because it optimizes the map at multiple levels of resolution. The resulting algorithm has an update time that is linear in the number of estimated features for typical indoor environments, even when closing very large loops, and offers advantages in handling non-linearities compared to other SLAM algorithms. Experimental comparisons with alternative algorithms using two well-known data sets and mapping results on a real robot are also presented

  • 13.
    Jun, Li
    et al.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Q-Learning with a growing RBF network for behavior learning in mobile robotics2005Ingår i: Proceedings,  IASTED International Conference on Robotics and Applications: RA 2005 / [ed] L. A. Gerhardt, 2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    The use of artificial neural networks for approximating value functions in reinforcement learning is a common practice, but usually requires much work on designing the network architecture and refining of the network parame ters. In this paper we present a simple learning system that uses Q-learning with a resource allocating network (RAN) for behaviour learning in mobile robotics. The resource allocating network is used as a function approximator to dynamically represent the continuous sensory space, thus acquiring the sensorimotor mapping for generalization; and Q-learning is used to learn the control policy in ‘off-policy’ fashion that enables the human operator to guide the initial learning process, thus speeding up the reinforcement learn ing. We illustrate our approach using a PeopleBot robot to acquire a wall-following behaviour, and discuss some ob servations on the convergence and online training of our learning algorithm in the experiments.

  • 14.
    Jun, Li
    et al.
    Örebro universitet, Institutionen för teknik.
    Lilienthal, Achim J.
    Örebro universitet, Institutionen för teknik.
    Martìnez-Marìn, Tomas
    Department of Physics, System Engineering and Signal Theory, University of Alicante, Alicante, Spain.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Q-RAN: a constructive reinforcement learning approach for robot behavior learning2006Ingår i: 2006 IEEE/RSJ international conference on intelligent robots and systems, New York, NY, USA: IEEE, 2006, s. 2656-2662, artikel-id 4058792Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents a learning system that uses Q-learning with a resource allocating network (RAN) for behavior learning in mobile robotics. The RAN is used as a function approximator, and Q-learning is used to learn the control policy in `off-policy' fashion that enables learning to be bootstrapped by a prior knowledge controller, thus speeding up the reinforcement learning. Our approach is verified on a PeopleBot robot executing a visual servoing based docking behavior in which the robot is required to reach a goal pose. Further experiments show that the RAN network can also be used for supervised learning prior to reinforcement learning in a layered architecture, thus further improving the performance of the docking behavior.

  • 15.
    Li, Jun
    et al.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Growing RBF networks for learning reactive behaviours in mobile robotics2006Ingår i: International journal of vehicle autonomous systems, ISSN 1471-0226, Vol. 4, nr 2/3/4, s. 285-307Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper investigates a learning system based on growing Radial Basis Function (RBF) networks for acquiring reactive behaviours in mobile robotics. The learning algorithm integrates unsupervised and supervised learning, directly mapping the sensor information to the required motor action. The learning system is evaluated through a number of experiments on a real robot. The experimental results show that our learning system can learn a wide range of robot behaviours from simple tasks to complex tasks and demonstrate that the task need not be known at the programming time. This means that many different behaviours could potentially be acquired by the same learning architecture, thus dramatically reducing the development cost of autonomous robotic systems

  • 16.
    Lilienthal, Achim J.
    et al.
    University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    A stereo electronic nose for a mobile inspection robot2003Ingår i: ROSE 2003 - 1st IEEE International Workshop on Robotic Sensing 2003, IEEE, 2003, artikel-id 1218709Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper describes the design of a gas-sensitive system that is suitable for use on a mobile robot ("mobile nose"). The stereo architecture comprises two equivalent sets of gas sensors mounted inside separated ventilated tubes (or "nostrils"). To characterise the dynamic response, the whole system is modelled as a first-order sensor. The corresponding parameters, including the response and recovery time, can be obtained by fitting this model to the values recorded during a simple experiment described in this paper. Our experiments confirmed the suitability of the applied model and permitted a quantitative comparison of different set-ups. It is shown that using suction fans lowers the recovery time of the metal oxide gas sensors by a factor of two, while a solid separation between the tubes (a "septum") is necessary to maintain the sensitivity of the mobile nose to concentration gradients.

  • 17.
    Lilienthal, Achim J.
    et al.
    University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    An absolute positioning system for 100 euros2003Ingår i: ROSE 2003 - 1st IEEE International Workshop on Robotic Sensing 2003: Sensing and Perception in 21st Century Robotics: Sensing and Perception in 21st Century Robotics, IEEE, 2003, artikel-id 1218705Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper describes an absolute positioning system, which provides accurate and reliable measurements using low-cost equipment that is easy to set up. The system uses a number of fixed web-cameras to track a distinctly coloured object. In order to calculate the (x,y) position of this object, estimates calculated by triangulation from each combination of two cameras are combined, resulting in centimeter-level accuracy. Example applications, including tracking of mobile robots and persons, are described. An extended set-up is also introduced, which allows determination of the heading of a two coloured object from single images

  • 18.
    Lilienthal, Achim J.
    et al.
    WSI, University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Approaches to gas source tracing and declaration by pure chemo-tropotaxis2003Ingår i: Autonome Mobile Systeme 2003 / [ed] Rüdiger Dillmann, Heinz Wörn, Tilo Gockel, Springer Berlin/Heidelberg, 2003, Vol. 18, s. 161-171Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of localising a static gas source in an uncontrolled indoor environment by a mobile robot. In contrast to previous works, especially the condition of an environment that is not artificially ventilated to produce a strong unidirectional airflow is considered. Here, the propagation of the analyte molecules is dominated by turbulence and convection flow rather than diffusion, thus creating a patchy distribution of spatially distributed eddies. Positive and negative tropotaxis, based on the spatial concentration gradient measured by a pair of electrochemical gas sensor arrays, were investigated. Both strategies were implemented utilising a direct sensor-motor coupling (a Braitenberg vehicle) and were shown to be useful to accomplish the gas source localisation task. As a possible solution to the problem of gas source declaration (the task of determining with certainty that the gas source has been found), an indirect localisation strategy based on exploration and concentration peak avoidance is suggested. Here, a gas source is located by exploiting the fact that local concentration maxima occur more frequently near the gas source compared to distant regions

  • 19.
    Lilienthal, Achim J.
    et al.
    University of Tübingen, WSI, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Building gas concentration gridmaps with a mobile robot2004Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 48, nr 1, s. 3-16Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of mapping the structure of a gas distribution by creating concentration gridmaps from the data collected by a mobile robot equipped with gas sensors. By contrast to metric gridmaps extracted from sonar or laser range scans, a single measurement from a gas sensor provides information about a comparatively small area. To overcome this problem, a mapping technique is introduced that uses a Gaussian weighting function to model the decreasing likelihood that a particular reading represents the true concentration with respect to the distance from the point of measurement. This method is evaluated in terms of its suitability regarding the slow response and recovery of the gas sensors, and experimental comparisons of different exploration strategies are presented. The stability of the mapped structures and the capability to use concentration gridmaps to locate a gas source are also discussed.

  • 20.
    Lilienthal, Achim J.
    et al.
    University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Creating gas concentration gridmaps with a mobile robot2003Ingår i: Proceedings: 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003), New York, USA: IEEE, 2003, Vol. 3, s. 118-123Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of mapping the features of a gas distribution by creating concentration gridmaps from the data collected by a mobile robot equipped with an electronic nose. By contrast to metric gridmaps extracted from sonar or laser range scans, a single measurement of the electronic nose provides information about a comparatively small area. To overcome this problem, a mapping technique is introduced that uses a Gaussian density function to model the decreasing likelihood that a particular reading represents the true concentration with respect to the distance from the point of measurement. This method is evaluated in terms of its suitability regarding the slow response and recovery of the gas sensors. The stability of the mapped features and the capability to use concentration gridmaps to locate a gas source are also discussed.

  • 21.
    Lilienthal, Achim J.
    et al.
    W.-Schickard-Inst. for Comp. Science, University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Experimental analysis of gas-sensitive Braitenberg vehicles2004Ingår i: Advanced Robotics, ISSN 0169-1864, E-ISSN 1568-5535, Vol. 18, nr 8, s. 817-834Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article addresses the problem of localising a static gas source in an indoor environment by a mobile robot. In contrast to previous works, the environment is not artificially ventilated to produce a strong unidirectional airflow. Here, the dominant transport mechanisms of gas molecules are turbulence and convection flow rather than diffusion, which results in a patchy, chaotically fluctuating gas distribution. Two Braitenberg-type strategies (positive and negative tropotaxis) based on the instantaneously measured spatial concentration gradient were investigated. Both strategies were shown to be of potential use for gas source localisation. As a possible solution to the problem of gas source declaration (the task of determining with certainty that the gas source has been found), an indirect localisation strategy based on exploration and concentration peak avoidance is suggested. Here, a gas source is located by exploiting the fact that local concentration maxima occur more frequently near the gas source compared to distant regions

  • 22.
    Lilienthal, Achim J.
    et al.
    University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Experimental analysis of smelling Braitenberg vehicles2003Ingår i: Proceedings of the 11th International Conference on Advanced Robotics 2003, Coimbra, Portugal: Coimbra, University , 2003, Vol. 1-3, s. 375-380Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of localisation of a static odour source in an unstructured indoor environment by a mobile robot using electrochemical gas sensors. In particular, reactive localisation strategies based on the instantaneously measured spatial concentration gradient are considered. In contrast to previous works, the environment is not artificially ventilated to produce a strong constant airflow, and thus the distribution of the odour molecules is dominated by turbulence. An experimental set-up is presented that enables different strategies for odour source localisation to be compared directly in a precisely measured experiment. Two alternative strategies that utilise a direct sensor-motor coupling are then investigated and a detailed numerical analysis of the results is presented, including tests of statistical significance. Both tested strategies proved to be useful to accomplish the localisation task. As a possible solution to the problem of detecting that the odour source - which is usually not corresponding to the global concentration maximum - was found, one of the tested strategies exploits the fact that local concentration maxima occur more frequently near the odour source compared to distant regions

  • 23.
    Lilienthal, Achim J.
    et al.
    University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Gas source localisation by constructing concentration gridmaps with a mobile robot2003Ingår i: Proceedings of the European conference on mobile robots: ECMR 2003, 2003, s. 159-164Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of mapping the features of a gas distribution by creating concentration gridmaps with a mobile robot equipped with a gas-sensitive system ("mobile nose"). By contrast to metric gridmaps extracted from sonar or laser range scans, a gas sensor measurement provides information about a comparatively small area. To overcome this problem, a mapping technique is introduced that uses a Gaussian density function to model the decreasing likelihood that a particular reading represents the true concentration with respect to the distance from the point of measurement. The structure of the mapped features is discussed with respect to the parameters of the applied density function, the evolution of the gas distribution over time, and the capability to locate a gas source.

  • 24.
    Lilienthal, Achim J.
    et al.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Ishida, Hiroshi
    Tokyo Univ. of Agriculture and Technology, Dept. of Mechanical Systems Engineering, Tokyo, Japan.
    Werner, Felix
    Wilhelm-Schickard Institute, University of Tübingen, Tübingen, Germany.
    Indicators of gas source proximity using metal oxide sensors in a turbulent environment2006Ingår i: The First IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics, 2006, BioRob 2006, New York, NY, USA: IEEE, 2006, s. 733-738, artikel-id 1639177Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper addresses the problem of estimating proximity to a gas source using concentration measurements. In particular, we consider the problem of gas source declaration by a mobile robot equipped with metal oxide sensors in a turbulent indoor environment. While previous work has shown that machine learning classifiers can be trained to detect close proximity to a gas source, it is difficult to interpret the learned models. This paper investigates possible underlying indicators of gas source proximity, comparing three different statistics derived from the sensor measurements of the robot. A correlation analysis of 1056 trials showed that response variance (measured as standard deviation) was a better indicator than average response. An improved result was obtained when the standard deviation was normalized to the average response for each trial, a strategy that also reduces calibration problems.

  • 25.
    Loutfi, Amy
    et al.
    Örebro universitet, Institutionen för teknik.
    Coradeschi, Silvia
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Wide, Peter
    Örebro universitet, Institutionen för teknik.
    Odor source identification by grounding linguistic descriptions in an artificial nose2001Ingår i: Proceedings of the the sensor fusion conference: architectures, algorithms, and applications, 2001, s. 273-281Konferensbidrag (Övrigt vetenskapligt)
    Abstract [en]

    This paper addresses the problem of enabling autonomous agents (e.g., robots) to carry out human oriented tasks using an electronic nose. The nose consists of a combination of passive gas sensors with different selectivity, the outputs of which are fused together with an artificial neural network in order to recognize various human-determined odors. The basic idea is to ground human-provided linguistic descriptions of these odors in the actual sensory perceptions of the nose through a process of supervised learning. Analogous to the human nose, the paper explains a method by which an electronic nose can be used for substance identification. First, the receptors of the nose are exposed to a substance by means of inhalation with an electric pump. Then a chemical reaction takes place in the gas sensors over a period of time and an artificial neural network processes the resulting sensor patterns. This network was trained to recognize a basic set of pure substances such as vanilla, lavender and yogurt under controlled laboratory conditions. The complete system was then validated through a series of experiments on various combinations of the basic substances. First, we showed that the nose was able to consistently recognize unseen samples of the same substances on which it had been trained. In addition, we presented some first results where the nose was tested on novel combinations of substances on which it had not been trained by combining the learned descriptions - for example, it could distinguish lavender yogurt as a combination of lavender and yogurt.

  • 26.
    Magnusson, Martin
    et al.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    A comparison of 3D registration algorithms for autonomous underground mining vehicles2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    The ICP algorithm and its derivatives is the de facto standard for registration of 3D range-finder scans today. This paper presents a quantitative comparison between ICP and 3D NDT, a novel approach based on the normal distributions transform. The new method ad- dresses two of the main problems of ICP: the fact that it does not make use of the local surface shape and the computationally demanding nearest-neighbour search. The results show that 3D NDT produces accurate results much faster, though it is more sensitive to error in the initial pose estimate.

  • 27.
    Magnusson, Martin
    et al.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Elsrud, Rolf
    ̈Atlas Copco Rock Drills.
    Skagerlund, Lars-Erik
    Optab.
    3D modelling for underground mining vehicles2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents the basis of a new system for making detailed 3D models of underground tunnels. The system is to be used for automated control of mining vehicles. We describe some alternative methods for matching several partial scans, and their applicability for making a complete model of a mine environment

  • 28.
    Marsland, Stephen
    et al.
    University of Manchester.
    Nehmzow, Ulrich
    The University of Essex.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Learning to select distinctive landmarks for mobile robot navigation2001Ingår i: Robotics and Autonomous Systems, ISSN 0921-8890, E-ISSN 1872-793X, Vol. 37, nr 4, s. 241-260Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In landmark-based navigation systems for mobile robots, sensory perceptions (e.g., laser or sonar scans) are used to identify the robot’s current location or to construct internal representations, maps, of the robot’s environment. Being based on an external frame of reference (which is not subject to incorrigible drift errors such as those occurring in odometry-based systems), landmark-based robot navigation systems are now widely used in mobile robot applications.

    The problem that has attracted most attention to date in landmark-based navigation research is the question of how to deal with perceptual aliasing, i.e., perceptual ambiguities. In contrast, what constitutes a good landmark, or how to select landmarks for mapping, is still an open research topic. The usual method of landmark selection is to map perceptions at regular intervals, which has the drawback of being inefficient and possibly missing ‘good’ landmarks that lie between sampling points.

    In this paper, we present an automatic landmark selection algorithm that allows a mobile robot to select conspicuous landmarks from a continuous stream of sensory perceptions, without any pre-installed knowledge or human intervention during the selection process. This algorithm can be used to make mapping mechanisms more efficient and reliable. Experimental results obtained with two different mobile robots in a range of environments are presented and analysed.

  • 29.
    Munkevik, Per
    et al.
    Örebro universitet, Institutionen för teknik.
    Hall, Gunnar
    The Swedish Institute for Food and Biotechnology.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Quality control of meal components by appearance-based novelty detection2006Ingår i: Industries Alimentaires et Agricoles, ISSN 0019-9311, Vol. 123, nr 3, s. 11-15Artikel i tidskrift (Refereegranskat)
  • 30.
    Saffiotti, Alessandro
    et al.
    Örebro universitet, Institutionen för teknik.
    Driankov, Dimiter
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    A system for vision based human-robot interaction2004Konferensbidrag (Refereegranskat)
    Abstract [en]

    We describe our initial steps toward the realization of a robotic system for assisting fire-fighting and rescue services. The system implements the concept of shared autonomy between the robot and the human operator: the mobile robot performs local navigation, sensing and mapping, while the operator interprets the sensor data and provides strategic navigation goals.

  • 31.
    Skoglund, Alexander
    et al.
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Iliev, Boyko
    Örebro universitet, Institutionen för teknik.
    Lilienthal, Achim J.
    Örebro universitet, Institutionen för teknik.
    Palm, Rainer
    Örebro universitet, Institutionen för teknik.
    Teaching by demonstration of robotic manipulators in non-stationary environments2006Ingår i: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) ,2006, IEEE, 2006, s. 4339-4341Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we propose a system consisting of a manipulator equipped with range sensors, that is instructed to follow a trajectory demonstrated by a human teacher wearing a motion capturing device. During the demonstration a three dimensional occupancy grid of the environment is built using the range sensor information and the trajectory. The demonstration is followed by an exploration phase, where the robot undergoes self-improvement of the task, during which the occupancy grid is used to avoid collisions. In parallel a reinforcement learning (RL) agent, biased by the demonstration, learns a point-to-point task policy. When changes occur in the workspace, both the occupancy grid and the learned policy will be updated online by the system.

  • 32.
    Skoglund, Alexander
    et al.
    Örebro universitet, Institutionen för teknik.
    Palm, Rainer
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Towards a supervised dyna-Q application on a robotic manipulator2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    Having a robot that can learn from and improve upon a human demonstration is a challenge for robotic scientists, and useful for non-engineers who want a robotic assistant to perform a particular task. In this paper we address some of the difficulties one will have to overcome when developing such a system for an articulated manipulator with more degrees-offreedom (d.o.f.) than most mobile robots on wheels. Making a good data capture of what is shown to the robot is one such problem. Another key scientific challenge is the curse of dimensionality that arises from the high dimensional state and action spaces in this application, which we propose to address by combination of supervised and reinforcement learning to gain benefits from both paradigms. We also point out that one has to be careful when trying to obtain an agent that learns a task in as few trials as possible, since it might require much more computational time.

  • 33.
    Tamimi, Hashem
    et al.
    University of Tubingen.
    Andreasson, Henrik
    Örebro universitet, Institutionen för teknik.
    Treptow, André
    University of Tubingen.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Zell, Andreas
    University of Tubingen.
    Localization of mobile robots with omnidirectional vision using particle filter and iterative SIFT2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    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

  • 34.
    Treptow, André
    et al.
    University of Tubingen.
    Cielniak, Grzegorz
    Örebro universitet, Institutionen för teknik. AASS.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Active people recognition using thermal and grey images on a mobile security robot2005Ingår i: 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2005. (IROS 2005): IROS 2005 IEEE/RSJ -, 2005, s. 2103-2108Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper we present a vision-based approach to detect, track and identify people on a mobile robot in real time. While most vision systems for tracking people on mobile robots use skin color information, we present an approach using thermal images and a fast contour model together with a Particle Filter. With this method a person can be detected independently from current light conditions and in situations were no skin color is visible (the person is not close or does not face the robot). Tracking in thermal images is used as an attention system to get an estimate of the position of a person. Based on this estimate we use a pan-tilt camera to zoom to the expected face region and apply a fast face tracker in combination with face recognition to identify the person.

  • 35.
    Treptow, André
    et al.
    University of Tubingen.
    Cielniak, Grzegorz
    Örebro universitet, Institutionen för teknik.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Comparing measurement models for tracking people in thermal images on a mobile robot2005Konferensbidrag (Refereegranskat)
    Abstract [en]

    While most vision systems for tracking people on mobile robots use skin color information, we present an approach using thermal images and two different measurement models together with a Particle Filter. With this method a person can be detected independently from current light conditions and in situations were no skin color is visible (the person is not close or does not face the robot). The results show that a measurement model that was learned from local greyscale features improved on the performance of an elliptic contour model, and that both models could be used in combination to further improve performance with minimal extra computational cost

  • 36.
    Wandel, Michael
    et al.
    University of Tübingen, Tübingen, Germany.
    Lilienthal, Achim J.
    University of Tübingen, Tübingen, Germany.
    Duckett, Tom
    Örebro universitet, Institutionen för teknik.
    Weimar, Udo
    University of Tübingen, Tübingen, Germany.
    Zell, Andreas
    University of Tübingen, Tübingen, Germany.
    Gas distribution in unventilated indoor environments inspected by a mobile robot2003Ingår i: Proceedings of the IEEE international conference on advanced robotics 2003, Coimbra, Portugal: University of Coimbra , 2003, Vol. 1-3, s. 507-512Konferensbidrag (Refereegranskat)
    Abstract [en]

    Gas source localisation with robots is usually performed in environments with a strong, unidirectional airflow created by artificial ventilation. This tends to create a strong, well defined analyte plume and enables upwind searching. By contrast, this paper presents experiments conducted in unventilated rooms. Here, the measured concentrations also indicate an analyte plume with, however, different properties concerning its shape, width, concentration profile and stability over time. In the results presented in this paper, two very different mobile robotic systems for odour sensing were investigated in different environments, and the similarities as well as differences in the analyte gas distributions measured are discussed.

1 - 36 av 36
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