Journal of Intelligent & Fuzzy Systems - Volume 15, issue 1

Article Type: Other

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 1-1, 2004

Authors: Heintz, Fredrik | Doherty, Patrick

Article Type: Research Article

Abstract: Any autonomous system embedded in a dynamic and changing environment must be able to create qualitative knowledge and object structures representing aspects of its environment on the fly from raw or preprocessed sensor data in order to reason qualitatively about the environment. These structures must be managed and made accessible to deliberative and reactive functionalities which are dependent on being situationally aware of the changes in both the robotic agent's embedding and internal environment. DyKnow is …a software framework which provides a set of functionalities for contextually accessing, storing, creating and processing such structures. The system is implemented and has been deployed in a deliberative/reactive architecture for an autonomous unmanned aerial vehicle. The architecture itself is distributed and uses real-time CORBA as a communications infrastructure. We describe the system and show how it can be used in execution monitoring and chronicle recognition scenarios for UAV applications. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 3-13, 2004

Authors: Togelius, Julian

Article Type: Research Article

Abstract: An approach to robotics called layered evolution and merging features from the subsumption architecture into evolutionary robotics is presented, and its advantages are discussed. This approach is used to construct a layered controller for a simulated robot that learns which light source to approach in an environment with obstacles. The evolvability and performance of layered evolution on this task is compared to (standard) monolithic evolution, incremental and modularised evolution. To corroborate the hypothesis that a …layered controller performs at least as well as an integrated one, the evolved layers are merged back into a single network. On the grounds of the test results, it is argued that layered evolution provides a superior approach for many tasks, and it is suggested that this approach may be the key to scaling up evolutionary robotics. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 15-20, 2004

Authors: Cielniak, Grzegorz | Duckett, Tom

Article Type: Research Article

Abstract: 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. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 21-27, 2004

Authors: Grunditz, Carl-Henrik | Spaanenburg, Lambert

Article Type: Research Article

Abstract: Visual quality assurance techniques focus on the detection and qualification of abnormal structures in the image of an object. The features of abnormality are extracted through image mining, whereupon classification is performed on characteristic combinations. Many techniques for feature extraction have been proposed, but the feed-forward neural network is seldom utilized despite its popularity in other application areas. Based on the wide experience base, this paper shows how a multi-tier feed-forward network can be …constructed to model detectable peaks using only the physical properties of the image domain. This generic architecture can easily be adapted for different applications, as in metal plate inspection and protein detection, with mean error rate below 5%. Show more

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 29-39, 2004

Authors: Olsson, Erik | Funk, Peter | Xiong, Ning

Article Type: Research Article

Abstract: Fault diagnosis of industrial equipments becomes increasingly important for improving the quality of manufacturing and reducing the cost for product testing. Developing a fast and reliable diagnosis system presents a challenging issue in many complex industrial scenarios. The major difficulties therein arise from contaminated sensor readings caused by heavy background noise as well as the unavailability of experienced technicians for support. In this paper we propose a novel method for diagnosis of faults by means of …case-based reasoning and signal processing. The received sensor signals are processed by wavelet analysis to filter out noise and at the same time to extract a group of related features that constitutes a reduced representation of the original signal. The derived feature vector is then forwarded to a classification component that uses case-based reasoning to recommend a fault class for the probe case. This recommendation is based on previously classified cases in a case library. Case-based diagnosis has attractive properties in that it enables reuse of past experiences whereas it imposes no demand on the size of the case base. The proposed approach has been applied to fault diagnosis of industrial robots at ABB Robotics and the results of experiments are very promising. Show more

Keywords: case-based reasoning, fault diagnosis, feature extraction, signal filtering, wavelet analysis

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 41-46, 2004

Authors: van Veelen, Martijn | Spaanenburg, Lambert

Article Type: Research Article

Abstract: The past decade has witnessed a marked increase in distributed system complexity. This was driven by a maturing technology that steadily decreased the number of faults. Unfortunately these fewer faults have become exponentially more costly. It becomes mandatory to detect faults prior to taking effect on the network. Such an early detection requires a new test, detection and fault containment strategy, of which the outline and some basic ingredients are sketched here.

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 47-59, 2004

Authors: Larsson, Jan Eric | Ahnlund, Jonas | Bergquist, Tord | Dahlstrand, Fredrik | Öhman, Bengt | Spaanenburg, Lambert

Article Type: Research Article

Abstract: Multilevel flow modeling (MFM) is a modeling method for complex technical systems in which the goals and functions of the system are explicitly described. MFM can be used as a basis for root cause analysis, where primary root causes are separated from consequential faults, in complex fault situations. Model representations for use in diagnostic reasoning usually describe causality, between parameters, faults, or process states. However, the causality of a system may vary depending on details …in the construction, as well as over time with the process state. One contribution of this paper is a general method of describing varying causality in a simple and efficient way. The method has been tested using multilevel flow models. Causality is visible in measurements and can be used to increase process understanding. The standard cross-correlation technique is insufficient for causality detection in industrial processes. Another contribution of this paper is a new method that can detect causality in industrial signals, and thus be used to validate the design of multilevel flow models. Show more

Keywords: alarm analysis, causality, complex technical systems, correlation, multilevel flow models, fault detection, root cause analysis

Citation: Journal of Intelligent & Fuzzy Systems, vol. 15, no. 1, pp. 61-73, 2004