Topological SLAM using neighbourhood information of places

Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM~(simultaneous localisation and mapping) which does not require motion or odometry information but only a sequence of noisy measurements from visited places. We propose a particle filtering technique for topological SLAM which relies on a method for disambiguating places which appear indistinguishable using neighbourhood information extracted from the sequence of observations. The algorithm aims to induce a small topological map which is consistent with the observations and simultaneously estimate the location of the robot. The proposed approach is evaluated using a data set of sonar measurements from an indoor environment which contains several similar places. It is demonstrated that our approach is capable of dealing with severe ambiguities and, and that it infers a small map in terms of vertices which is consistent with the sequence of observations.

A multi-hypothesis topological SLAM approach for loop closing on edge-ordered graphs

We present a method for topological SLAM that specifically targets loop closing for edge-ordered graphs. Instead of using a heuristic approach to accept or reject loop closing, we propose a probabilistically grounded multi-hypothesis technique that relies on the incremental construction of a map/state hypothesis tree. Loop closing is introduced automatically within the tree expansion, and likely hypotheses are chosen based on their posterior probability after a sequence of sensor measurements. Careful pruning of the hypothesis tree keeps the growing number of hypotheses under control and a recursive formulation reduces storage and computational costs. Experiments are used to validate the approach.

The role of organisational capacity in the knowledge-based transformation of Brisbane, Australia

Purpose - The cumulative impacts of the knowledge economy together with the emerging dominance of knowledge-intensive sectors, have led to an unprecedented period of socio-economic and spatial restructuring. As a result, the paradigm of knowledge-based urban development (KBUD) has emerged as a development strategy to guide knowledge-based economic transformation (Knight, 1995; Yigitcanlar, 2007). Notwithstanding widespread government commitment and financial investment, in many cases providing the enabling circumstances for KUBUD has proven a complicated task as institutional barriers remain. Researchers and practitioners advocate that the way organisations work and their institutional relationships, policies and programs, will have a significant impact on a regions capacity to achieve KBUD (Savitch, 1998; Savitch and Kantor, 2002; Keast and Mandell, 2009). In this context, building organisational capacity is critical to achieving institutional change and bring together all of the key actors and sources, for the successful development, adoption, and implementation of knowledge-based development of a city (Yigitcanlar, 2009). Design/methodology/approach - There is a growing need to determine the complex inter-institutional arrangements and intra-organisational interactions required to advance urban development within the knowledge economy. In order to design organisational capacity-building strategies, the associated attributes of good capacity must first be identified. The paper, with its appraisal of knowledge-based urban development, scrutinises organisational capacity and institutional change in Brisbane. As part of the discussion of the case study findings, the paper describes the institutional relationships, policies, programs and funding streams, which are supporting KBUD in the region. Originality/value - In consideration that there has been limited investigation into the institutional lineaments required to provide the enabling circumstances for KBUD, the broad aim of this paper is to discover some good organisational capacity attributes, achieved through a case study of Brisbane. Practical implications - It is anticipated that the findings of the case study will contribute to moving the discussion on the complex inter-institutional arrangements and intra-organisaational interactions required for KBUD, beyond a position of rhetoric.

Modeling and multiway analysis of chatroom tensors

This work identifies the limitations of n-way data analysis techniques in multidimensional stream data, such as Internet chat room communications data, and establishes a link between data collection and performance of these techniques. Its contributions are twofold. First, it extends data analysis to multiple dimensions by constructing n-way data arrays known as high order tensors. Chat room tensors are generated by a simulator which collects and models actual communication data. The accuracy of the model is determined by the Kolmogorov-Smirnov goodness-of-fit test which compares the simulation data with the observed (real) data. Second, a detailed computational comparison is performed to test several data analysis techniques including svd [1], and multi-way techniques including Tucker1, Tucker3 [2], and Parafac [3].