CAIR - the Centre for Artificial Intelligence Research

Permanent link for this collection

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.

Browse

Now showing 1 - 5 of 10

Autonomous Robot Mapping by Landmark Association
(CEUR-WS.org, 2015) Azizzul, Z; Yeap, W; Airenti, G; Bara, BG; Sandini, G
This paper shows how an indoor mobile robot equipped with a laser sensor and an odometer computes its global map by associating landmarks found in the environment. The approach developed is based on the observation that humans and animals detects where they are in the surrounding by comparing their spatial relation to some known or recognized objects in the environments, i.e. landmarks. In this case, landmarks are defined as 2D surfaces detected in the robot’s surroundings. They are recognised if they are detected in two successive views. From a cognitive standpoint, this work is inspired by two assumptions about the world; (a) the world is relatively stable and (2) there is a significant overlap of spatial information between successive views. In the implementation, the global map is first initialised with the robot’s first view, and then updated each time landmarks are found at every two successive views. The difference here is, where most robot mapping work integrates everything they see in their update, this work takes advantage of updating only the landmarks before adding the nearby objects associated with them. By association, the map is built without error corrections and the final map produced is not metrically precise.
The Correspondence Problem in Topological Metric Mapping – Using Absolute Metric Maps to Close Cycles
(Springer, 2004) Jefferies, M.; Cosgrove, M.; Baker, J.; Yeap, W.
In Simultaneous Localisation and Mapping (SLAM) the correspondence problem, specifically detecting cycles, is one of the most difficult challenges for an autonomous mobile robot. In this paper we show how significant cycles in a topological map can be identified with a companion absolute global metric map. A tight coupling of the basic unit of representation in the two maps is the key to the method. Each local space visited is represented, with its own frame of reference, as a node in the topological map. In the global absolute metric map these local space representations from the topological map are described within a single global frame of reference. The method exploits the overlap which occurs when duplicate representations are computed from different vantage points for the same local space. The representations need not be exactly aligned and can thus tolerate a limited amount of accumulated error. We show how false positive overlaps which are the result of a misaligned map, can be discounted. © Springer-Verlag 2004.
Using Absolute Metric Maps to Close Cycles in a Topological Map
(Springer, 2005) Jefferies, M.; Yeap, W.; Cosgrove, M.; Baker, J.
In simultaneous localisation and mapping (SLAM) the correspondence problem, specifically detecting cycles, is one of the most difficult challenges for an autonomous mobile robot. In this paper we show how significant cycles in a topological map can be identified with a companion absolute global metric map. A tight coupling of the basic unit of representation in the two maps is the key to the method. Each local space visited is represented, with its own frame of reference, as a node in the topological map. In the global absolute metric map these local space representations from the topological map are described within a single global frame of reference. The method exploits the overlap which occurs when duplicate representations are computed from different vantage points for the same local space. The representations need not be exactly aligned and can thus tolerate a limited amount of accumulated error. We show how false positive overlaps which are the result of a misaligned map, can be discounted. © 2005 Springer Science+Business Media, Inc.
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.
Pronominal Anaphora Resolution Using a Shallow Meaning Representation of Sentences
(Springer, 2004) Ho, H.; Min, K.; Yeap, W.
This paper describes a knowledge-poor anaphora resolution approach based on a shallow meaning representation of sentences. The structure afforded in such a representation provides immediate identification of local domains which are required for resolving pronominal anaphora. Other kinds of information used include syntactic information, structure parallelism and salience weights. We collected 111 singular 3rd person pronouns from open domain resources such as children's novel and examples from several anaphora resolution papers. There are 111 third-person singular pronouns in the experiment data set and 94 of them demonstrate pronominal anaphora in domain of test data. The system successfully resolves 78.4% of anaphoric examples. © Springer-Verlag Berlin Heidelberg 2004.

Browse

Recent Submissions