CAIR - the Centre for Artificial Intelligence Research

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https://hdl.handle.net/10292/550
Information Technology is a term that encompasses all forms of technology used to create and manipulate information in its various forms. The primary goal of the Centre for Artificial Intelligence Research (CAIR) is to provide strong leadership and a stimulating environment for the development of these different forms of technology in New Zealand. However, our desire is that our research will not be ivory-towered. Since AUT is the only university of technology in this country, this emphasis is an important one; our research must not only be at the leading edge but must also be practically useful.

Given the widely ranging possibilities of research in this area, the Centre has decided to stay focused in its foundation years. It has, in consultation with the School of Computing and Mathematical Sciences and KEDRI, decided to focus on three main areas of research and development work, namely human language technology, speech technology, and robotics.

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Browsing CAIR - the Centre for Artificial Intelligence Research by Author "Schmidt, J."

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    A Split & Merge Approach to Metric-Topological Map-Building
    (IEEE, 2006) Schmidt, J.; Wong, C.; Yeap, W.
    We present a novel split and merge based method for dividing a given metric map into distinct regions, thus effectively creating a topological map on top of a metric one. The initial metric map is obtained from range data that are convened to a geometric map consisting of linear approximations of the indoor environment. The splitting is done using an objective function that computes the quality of a region, based on criteria such as the average region width (to distinguish big rooms from corridors) and overall direction (which accounts for sharp bends). A regularization term is used in order to avoid the formation of very small regions, which may originate from missing or unreliable sensor data. Experiments based on data acquired by a mobile robot equipped with sonar sensors are presented, which demonstrate the capabilities of the proposed method. © 2006 IEEE.
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    Computing a Network of ASRs Using a Mobile Robot Equipped with Sonar Sensors
    (IEEE, 2006) Wong, C.; Yeap, W.; Schmidt, J.
    This paper presents a novel algorithm for computing absolute space representations (ASRs) [1]-[2] for mobile robots equipped with sonar sensors and an odometer. The robot is allowed to wander freely (i.e. without following any fixed path) along the corridors in an office environment from a given start point to an end point. It then wanders from the end point back to the start point. The resulting ASRs computed in both directions are shown. © 2006 IEEE.
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    Spatial Information Extraction for Cognitive Mapping with a Mobile Robot
    (Springer, 2007) Schmidt, J.; Wong, C.; Yeap, W.
    When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home. Humans naturally use more powerful heuristics while lower animals have shown to develop a variety of methods that tend to utilize two key pieces of information, namely distance and orientation information. Their methods differ depending on how they sense their environment. Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting "cognitive map" be used for localization? In this paper, we present an approach using a mobile robot to generate a "cognitive map", the main focus being on experiments conducted in large spaces that the robot cannot apprehend at once due to the very limited range of its sensors. The robot computes a "cognitive map" and uses distance and orientation information for localization. © Springer-Verlag Berlin Heidelberg 2007.
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    Using a Mobile Robot to Test a Theory of Cognitive Mapping
    (Springer, 2008) Yeap, W.; Wong, C.; Schmidt, J.
    This paper describes using a mobile robot, equipped with some sonar sensors and an odometer, to test navigation through the use of a cognitive map. The robot explores an office environment, computes a cognitive map, which is a network of ASRs [36, 35], and attempts to find its way home. Ten trials were conducted and the robot found its way home each time. From four random positions in two trials, the robot estimated the home position relative to its current position reasonably accurately. Our robot does not solve the simultaneous localization and mapping problem and the map computed is fuzzy and inaccurate with much of the details missing. In each homeward journey, it computes a new cognitive map of the same part of the environment, as seen from the perspective of the homeward journey. We show how the robot uses distance information from both maps to find its way home. © 2007 Springer-Verlag Berlin Heidelberg.
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