Ha, QP, Tran, T & Dissanayake, G 2005, 'A wavelet- and neural network-based voice interface system for wheelchair control', International Journal of Intelligent Systems Technologies and Applications, vol. 1, no. 1/2, pp. 49-65.
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Voice control has long been considered as a natural mechanism to assist powered wheelchair users. However, one implementation difficulty is that a voice input system may fail to recognise a user's voice. Indeed, speech activated interface between human and autonomous/semi-autonomous systems requires accurate detection and recognition. In this area pitch and end-point detection are of vital importance. This paper presents a new method for pitch detection based on the continuous wavelet transform phase. The proposed technique can serve as an accurate pitch detector, and also can offer an efficient solution to the end-point detection problem. The extracted features from a user's speech are then used to train a neural network for speech recognition. Experimental results are provided for the detection of pitch periods and end points and the recognition of a number of commands of male and female users. Laboratory tests are reported for the proposed voice control wheelchair system.
Ha, QP, Tran, TH & Dissanayake, G 2005, 'A wavelet- and neural network-based voice interface system for wheelchair control', International Journal of Intelligent Systems Technologies and Applications, vol. 1, no. 1-2, pp. 49-65.
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Voice control has long been considered as a natural mechanism to assist powered wheelchair users. However, one implementation difficulty is that a voice input system may fail to recognise a user’s voice. Indeed, speech activated interface between human and autonomous/semi-autonomous systems requires accurate detection and recognition. In this area pitch and end-point detection is of vital importance. This paper presents a new method for pitch detection based on the continuous wavelet transform phase. The proposed technique can serve as an accurate pitch detector, and also can offer an efficient solution to the end-point detection problem. The extracted features from a user’s speech are then used to train a neural network for speech recognition. Experimental results are provided for the detection of pitch periods and end points and the recognition of a number of commands of male and female users. Laboratory tests are reported for the proposed voice control wheelchair system. © 2005 Inderscience Enterprises Ltd.
Huang, S, James, M & Jiang, Z 2005, 'L-infinity-bounded robust control of nonlinear cascade systems', Systems & Control Letters, vol. 54, no. 3, pp. 215-224.
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In this paper, we consider the L-infinity-bounded robust control problem for a class of nonlinear cascade systems with disturbances. Sufficient conditions are provided under which a hard bound is imposed on the system performance measure. The backsteppin
Huang, S, James, M, Nesic, D & Dower, P 2005, 'A unified approach to controller design for achieving ISS and related properties', IEEE Transactions On Automatic Control, vol. 50, no. 11, pp. 1681-1697.
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A unified approach to the design of controllers achieving various specified input-to-state stability (ISS) like properties is presented. Both full state and measurement feedback cases are considered. Synthesis procedures based on dynamic programming are
Huang, S, James, M, Nesic, D & Dower, P 2005, 'Analysis of input-to-state stability for discrete time nonlinear systems via dynamic programming', Automatica, vol. 41, no. 12, pp. 2055-2065.
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The input-to-state stability (ISS) property for systems with disturbances has received considerable attention over the past decade or so, with many applications and characterizations reported in the literature. The main purpose of this paper is to presen
Kim, J & Sukkarieh, S 2005, '6DoF SLAM aided GNSS/INS navigation in GNSS denied and unknown environments', Positioning, vol. 1, pp. 0-0.
Takezawa, S, Gulrez, T, Herath, DC & Dissanayake, G 2005, 'Environmental recognition for autonomous robot using Simultaneous Localization and Map Building (SLAM) (real time path planning with dynamical localized voronoi diyision)', Nihon Kikai Gakkai Ronbunshu, C Hen/Transactions of the Japan Society of Mechanical Engineers, Part C, vol. 71, no. 3, pp. 904-911.
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The Goal of this work is to provide a more in depth understanding of the navigation in the autonomous robot using stable visual points derived from the repeated experimentation by the stereo vision in a natural featured environment. In order to identify the position of the robot as well as to establish the 3 D obstacle map under the unknown environment, we discuss the simultaneous stereo type localization and map building (SLAM) problem. The design of the planning algorithm for a vision guided mobile robot depends upon the two main characteristics of visual environmental recognition i.e. Uncertainty and Efficiency. The uncertainty is reduced by the Extended Kalman Filter algorithm based on the process and observation model of the mobile robot. Regarding the efficiency, the optimal path planning algorithm which uses the dynamical localized Voronoi division is a new concept in our proposal. This method has the ability to make the path for mobile robot with only suitable number of natural features.
Tan, K, Chen, YJ, Wang, L & Liu, D 2005, 'Intelligent sensor fusion and learning for autonomous robot navigation', Applied Artificial Intelligence, vol. 19, no. 5, pp. 433-456.
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This paper presents the design and implementation of an autonomous robot navigation system for intelligent target collection in dynamic environments. A feature-based multi-stage fuzzy logic (MSFL) sensor fusion system is developed for target recognition, which is capable of mapping noisy sensor inputs into reliable decisions. The robot exploration and path planning are based on a grid map oriented reinforcement path learning system (GMRPL), which allows for long-term predictions and path adaptation via dynamic interactions with physical environments. In our implementation, the MSFL and GMRPL are integrated into subsumption architecture for intelligent target-collecting applications. The subsumption architecture is a layered reactive agent structure that enables the robot to implement higher-layer functions including path learning and target recognition regardless of lower-layer functions such as obstacle detection and avoidance. The real-world application using a Khepera robot shows the robustness and flexibility of the developed system in dealing with robotic behaviors such as target collecting in the ever-changing physical environment.
Tan, YG, Liu, DK, Liu, F & Zhou, ZD 2005, 'Digital robust preview control of path tracking', PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING, vol. 219, no. I1, pp. 111-117.
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Wang, J 2005, 'Tropospheric Delay Estimation for Pseudolite Positioning', Journal of GPS, vol. 4, no. 1-2, pp. 106-112.
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Pseudolites, ground-based GPS signal transmitters, can significantly enhance the GPS satellite geometry or can even be an independent positioning system. However, as pseudolites are very close to the receivers, error effects are different from the traditional GPS and should be considered and modeled in a different way. Tropospheric delay is one of the largest error sources of pseudolite positioning, as pseudolite signal propagates through the lower troposphere which is very difficult to be modeled due to spatial variations in atmosphere. The objective of this research is to analyse pseudolite tropospheric delay modelling methods and to select the optimal tropospheric delay models for different applications. Several methods to estimate the tropospheric delay for pseudolite positioning are introduced and compared. One approach is to utilize single-differenced GPS tropospheric models. Another one is to compute the tropospheric delay as a function of the local refractivity along the pseudolite signal path. The ratio method used for Electronic Distance Measurement (EDM) can also be applied to estimate tropospheric delay. Experiments with simulation and real flight test data are conducted in this study to investigate the proposed methods. The advantages and limitations of each method are analysed. The mode defined by RTCA and its modification are suitable for a low elevation and short range application, such as LAAS and local ground based applications. Models derived from single-differenced NMF and Saastamoinen models perform well in long range and high elevation but have big bias in low elevation. And the model derived from the Hopfield model performs relatively well in all the range and elevation.
Wijesoma, WS, Kodagoda, KRS & Balasuriya, AP 2005, 'Laser-camera composite sensing for road detection and tracking', INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION, vol. 20, no. 3, pp. 145-157.
Wijesoma, WS, Kodagoda, S & Balasuriya, A 2005, 'Laser-camera composite sensing for road detection and tracing', International Journal of Robotics and Automation, vol. 20, no. 03, pp. 145-157.
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An important feature in most urban roads and similar environments, such as in theme parks, campus sites, industrial estates, science parks, and the like, is the existence of pavements or curbs on either side de?ning the road boundaries. These curbs, which are mostly parallel to the road, can be harnessed to extract useful features of the road for implementing autonomous navigation or driver assistance systems. However, vision-alone methods for extraction of such curbs or road edge features with accurate depth information is a formidable task, as the curb is not conspicuous in the vision image and also requires the use of stereo images. Further, bad lighting, adverse weather conditions, nonlinear lens aberrations, or lens glare due to sun and other bright light sources can severely impair the road image quality and thus the operation of vision-alone methods. In this paper an alternative and novel approach involving the fusion of 2D laser range and monochrome vision image data is proposed to improve the robustness and reliability. Experimental results are presented to demonstrate the viability and effectiveness of the proposed methodology and its robustness to different road configurations and shadows.
Zhang, N, Kirpitchenko, I & Liu, D 2005, 'Dynamic model of the grinding process', Journal Of Sound And Vibration, vol. 280, no. 1-2, pp. 425-432.
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Grinding is one of the most versatile methods of removing material from machine parts to provide precise geometry. Dynamic analysis of the grinding process is necessary to reduce the surface waviness and roughness induced by vibrations, and to offer a ma
Andrade-cetto, J, Vidal Calleja, TA & Sanfeliu, A 2005, 'Unscented Transformation Of Vehicle States In Slam', 2005 IEEE International Conference on Robotics and Automation (ICRA), Vols 1-4, IEEE International Conference on Robotics and Automation (ICRA), IEEE, Barcelona, SPAIN, pp. 323-328.
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In this article we propose an algorithm to reduce the effects caused by linearization in the typical EKF approach to SLAM. The technique consists in computing the vehicle prior using an Unscented Transformation. The UT allows a better nonlinear mean and
Bryson, M, Kim, J & Sukkarieh, S 2005, 'Information and observability metrics of inertial SLAM for on-line path-planning on an aerial vehicle', IEEE international conference on robotics and automation, Spain.
Fang, G, Dissanayake, G, Kwok, N & Huang, S 2005, 'Near Minimum Time Path Planning for Bearing-Only Localisation and Mapping', 2005 IEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, The Institute of Electrical and Electronic Engineers Inc, Edmonton, Canada, pp. 2763-2768.
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The main contribution of this paper is an algorithm for integrating motion planning and simultaneous localisation and mapping (SLAM). Accuracy of the maps and the robot locations computed using SLAM is strongly dependent on the characteristics of the environment, for example feature density, as well as the speed and direction of motion of the robot. Appropriate control of the robot motion is particularly important in bearing-only SLAM, where the information from a moving sensor is essential. In this paper a near minimum time path planning algorithm with a finite planning horizon is proposed for bearing-only SLAM. The objective of the algorithm is to achieve a predefined mapping precision while maintaining acceptable vehicle location uncertainty in the minimum time. Simulation results have shown the effectiveness of the proposed method.
Fitch, R, Butler, Z & Rus, D 2005, 'Reconfiguration planning among obstacles for heterogeneous self-reconfiguring robots', 2005 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-4, IEEE International Conference on Robotics and Automation (ICRA), IEEE, Barcelona, SPAIN, pp. 117-124.
Ha, QP, Tran, T, Scheding, S, Dissanayake, G & Durrant-Whyte, H 2005, 'Control Issues of an Autonomous Vehicle', Proceedings of the 22nd International Symposium on Automation and Robotics in Construction ISARC 2005, International Symposium of Automation and Robotics in Construction, Faculty of Architecture and Engineering, University of Ferrara, Farrara, Italy, pp. 1-7.
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Ha, QP, Trinh, HM & Dissanayake, G 2005, 'A Distributed Approach to Global Feedback Control of Multi-Agent Systems', Proceedings of the 6th International Symposium on Intelligent Technologies, International Symposium on Intelligent Technologies in Tech '05, Faculty of Science and Technology, Assumption University, Phuket, Thailand, pp. 67-72.
Huang, S, Kwok, N, Dissanayake, G, Ha, QP & Fang, G 2005, 'Multi-Step Look-Ahead Trajectory Planning in SLAM: Possibility and Necessity', Proceedings of 2005 IEEE International Conference on Robotics and Automation, IEEE International Conference on Robots and Automation, The Institute of Electrical and Electronic Engineers Inc, Barcelona, Spain, pp. 1103-1108.
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In this paper, the possibility and necessity of multistep trajectory planning in Extended Kalman Filter (EKF) based SLAM is investigated. The objective of the trajectory planning here is to minimize the estimation error of the robot and landmark locations subject to a given time horizon. We show that the problem can be regarded as an optimization problem for a gradually identified model. A numerical method is proposed for trajectory planning using a variant of the nonlinear Model Predictive Control (MPC). The proposed method is optimal in the sense that the control action is computed using all the information available at the time of decision making. Simulation results are included to compare the results from the one-step look-ahead trajectory planning and the proposed multi-step lookahead technique
Huang, SD, Kwok, NM, Dissanayake, G, Ha, QP & Fang, G 2005, 'Multi-step look-ahead trajectory planning in SLAM: Possibility and necessity', 2005 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-4, IEEE International Conference on Robotics and Automation (ICRA), IEEE, Barcelona, SPAIN, pp. 1091-1096.
Kim, J & Brambley, G 2005, 'Dual Optic-flow Integrated Inertial Navigation', Australasian Conference on Robotics and Automation.
Kim, J & Sukkarieh, S 2005, 'Towards robust airborne SLAM in unknown wind environments', Proceedings of the Australasian Conference on Robotics and Automation, pp. 15-19.
Kodagoda, S, Wang, C & Dissanayake, G 2005, 'Laser Based Sensing on Roads', Proceedings of the Intelligent Vehicles and Road Infrastructure Conference, Intelligent Vehicles & Road Infrastructure Conference, Society of Automotive Engineers, Australia, Melbourne, Australia, pp. 1-8.
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Kwok, N, Dissanayake, G & Ha, QP 2005, 'Bearing-only SLAM using a SPRT Based Gaussian Sum Filter', Proceedings of 2005 IEEE International Conference on Robotics and Automation, IEEE International Conference on Robotics and Automation, The IEEE, Barcelona Spain, pp. 1121-1126.
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Use of a Gaussian Sum filter (GSF) to efficiently solve the initialisation problem in bearing-only simultaneous localisation and mapping (SLAM) is the main contribution of this paper. When information about the range is not available, the initial probability density function (pdf) of a landmark in the environment can not be represented using a Gaussian. The GSF is an attractive candidate for estimation in this scenario as it can deal with arbitrary pdfs represented as sets of Gaussians. However, the implementation of the GSF requires maintaining a bank of extended Kalman filters. The resulting computational complexity needs to be reduced by employing a minimum number of filters. In this work, the performance of each extended Kalman filter (EKF) in the GSF is evaluated using the sequential probability ratio test (SPRT). As such the number of members in the Gaussian sum can be reduced rapidly and the efficiency of the GSF can be significantly increased, providing a solution to the important problem of bearing-only SLAM. The effectiveness of the proposed approach is demonstrated by simulation and experiment conducted using a Pioneer mobile robot.
Kwok, NM, Dissanayake, G & Ha, QP 2005, 'Bearing-only SLAM using a SPRT based Gaussian sum filter', 2005 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-4, IEEE International Conference on Robotics and Automation (ICRA), IEEE, Barcelona, SPAIN, pp. 1109-1114.
Lasky, V, Liu, D, Murray, SJ & Choy, KK 2005, 'A Remote PLC System for e-Learning', Proc of the 4th ASEE/AAEE Global Colloquium on Engineering Education, ASEE Global Colloquium of Engineering Education, AAEE, Sydney, Australia, pp. 1-10.
Lau, H, Huang, S & Dissanayake, G 2005, 'Optimal Search for Multiple Targets in a Built Environment', 2005 IEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE Press, Edmonton, Canada, pp. 228-233.
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The main contribution of this paper is an algorithm for autonomous search that minimizes the expected time for detecting multiple targets present in a known built environment. The proposed technique makes use of the probability distribution of the target(s) in the environment, thereby making it feasible to incorporate any additional information, known a-priori or acquired while the search is taking place, into the search strategy. The environment is divided into a set of distinct regions and an adjacency matrix is used to describe the connections between them. The costs of searching any of the regions as well as the cost of travel between them can be arbitrarily specified. The search strategy is derived using a dynamic programming algorithm. The effectiveness of the algorithm is illustrated using an example based on the search of an office environment. An analysis of the computational complexity is also presented.
Leung, C, Huang, S, Dissanayake, G & Furukawa, T 2005, 'Trajectory Planning for Multiple Robots in Bearing Only Target Localisation', 2005 IEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Edmonton, Canada, pp. 2312-2317.
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This paper provides a solution to the optimal trajectory planning problem in target localisation for multiple heterogeneous robots with bearing-only sensors. The objective here is to find robot trajectories that maximise the accuracy of the locations of the targets at a prescribed terminal time. The trajectory planning is formulated as an optimal control problem for a nonlinear system with a gradually identified model and then solved using nonlinear model predictive control (MPC). The solution to the MPC optimisation problem is computed through exhaustive expansion tree search (EETS) plus sequential quadratic programming (SQP). Simulations were conducted using the proposed methods. Results show that EETS alone performs considerably faster than EETS+SQP with only minor differences in information gain, and that a centralised approach outperforms a decentralised one in terms of information gain. We show that a centralised EETS provides a near optimal solution. We also demonstrate the significance of using a matrix to represent the information gathered.
McLachlan, S, Arblaster, JI, Liu, D, Valls Miro, J & Chenoweth, L 2005, 'A multi-stage shared control method for an intelligent mobility assistant', 2005 IEEE 9th International Conference On Rehabilitation Robotics, IEEE International Conference on Rehabilitation Robotics, IEEE, Chicago, USA, pp. 426-429.
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This paper presents a multi-stage shared control method (MSSC) which can be used to control the movement of a robotic mobility assistant designed to facilitate safe mobilization for people with unstable gait. The multi-stage control module consists of user intent, obstacle avoidance and fuzzy logic components. The user intent represents the persons commands. The obstacle avoidance component reads datarepresenting any obstacles in the vicinity of the assistant and uses the Vector Field Histogram (VFH) algorithm to select a suitable path to avoid any obstacles in the path of travel. The fuzzy logic component is responsible for merging the user intent and obstacle avoidance information such that the users request is satisfied to the highest extent possible. When an unsafe situation presents itself the users request(s) will be partially or wholly overridden so the assistant can return to a safe state. The system has been designed to be dynamically configurable so as to suit different users in terms of gait stability and strength, preferred speed of travel and level of control over the system. It has been tested both in a simulated environment and real-world operating conditions and has been shown to effectively avoid obstacles with minimal disruption to the user and their intent.
Singh, SP & Waldron, K 2005, 'Attitude Estimation for Dynamic Legged Locomotion Using Range and Inertial Sensors', Proceedings of 2005 IEEE International Conference on Robotics and Automation, IEEE International Conference on Robotics and Automation, IEEE, Barcelona, Spain, pp. 1663-1668.
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Legged robots offer exceptional mobility in uncharted terrains. Their dynamic nature yields unrivaled mobility, but serves to destabilize the motion estimation process that underlies legged operations. In particular, the discontinuous foot fall patterns and flight phases result in severe impulses, which, in turn, result in excessive accumulation of drift by inertial sensors. Ground range measurements, amongst several others, are robust to this drift yet are limited in application due to their low-bandwidth and sensitivity to ground conditions. In considering the attitude estimation problem for this dynamic legged locomotion, this paper develops a pose calculation method based on ground range measurements. This is used in conjunction with a hybrid Extended Kalman Filter that takes advantage of the ballistic nature of the flight phases. Results indicate that this combination provides rapid, robust estimates of attitude necessary for extended dynamic legged operations. In single leg experiments, which were conducted using low-cost sensing hardware, this method had an RMS error of < 1 °, half that of a non-hybrid EKF approach.
Takezawa, S & Dissanayake, G 2005, 'Simultaneous localisation and mapping problems in indoor environments with stereo vision', IECON 2005: THIRTY-FIRST ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY, VOLS 1-3, 31st Annual Conference of the IEEE-Industrial-Electronics-Society, IEEE, Raleigh, NC, pp. 1896-1901.
Valls Miro, J, Dissanayake, G & Zhou, W 2005, 'Vision-based SLAM using natural features in indoor environments', Proceedings of the 2005 International Conference on Intelligent Sensors, Sensor Networks and Information Processing Conference., International Conference on Intelligent Sensors, Sensor Networks and Information Processing, IEEE Publications, Melbourne, Australia, pp. 151-156.
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This paper presents a practical approach to solve the simultaneous localization and mapping (SLAM) problem for autonomous mobile platforms by using natural visual landmarks obtained from an stereoscopic camera. It is an attempt to depart from traditional sensors such as laser rangefinders in order to gain the many benefits of nature-inspired information-rich 3D vision sensors. Whilst this makes the system fully observable in that the sensor provide enough information (range and bearing) to compute the full 2D estate of the observed landmarks from a single position, it is also true that depth information is difficult to rely on, particularly on measurements beyond a few meters (in fact the full 3D estate is observable, but here robot motion is constrained to 2D and only the 2D problem is considered). The work presented here is an attempt to overcome such a drawback by tackling the problem from a partially measurable SLAM perspective in that only landmark bearing from one of the cameras is employed in the fusion estimation. Range information estimates from the stereo pair is only used during map building in the landmark initialization phase in order to provide a reasonably accurate initial estimate. An additional benefit of the approach presented here lies in the data association aspect of SLAM. The availability of powerful feature extraction algorithms from the vision community, such as SIFT, permits a more flexible SLAM implementation separated from feature representation, extraction and matching, essentially carrying out matching with minimal recourse to geometry.
Waldron, K, Enedah, CC & Gladstone, H 2005, 'Stiffness and Texture Perception for Teledermatology', Medicine Meets Virtual Reality 13: The Magical Next Becomes the Medical Now, Medicine Meets Virtual Reality, IOS Press Fairfax, Virginia, pp. 579-585.
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The goal of the teledermatology project currently being carried out at Stanford University is to deliver tactile images of the human skin to a dermatologist at a remote location, in real time. In order to make a diagnosis, dermatologists typically need to obtain data regarding the skin texture and the mechanical properties of any lesions on a patient's skin. For example, pre-cancerous or weather-damaged skin typically feels rougher than normal skin and the profile and stiffness of the underlying tissue may shed light on the nature of a skin disease.
Wang, D, Liu, D, Wu, X & Tan, K 2005, 'A Force Field Method for Robot Navigation', Proceedings of the 3rd International Conference on Computational Intelligence, Robotics and Autonomous Systems, International Conference on Computational Intelligence, Robotics and Autonomous Systems, CIRAS & FIRA Organising Committee 2005, Singapore, pp. 1-6.
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Wang, JJ 2005, 'Modeling and geometry design for pseudolite augmented airborne DGPS', Proceedings of the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation, ION GNSS 2005, pp. 2076-2082.
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Carrier phase DGPS systems have been increasingly used in airborne surveying. However, the accuracy and availability of GPS positioning cannot meet the stringent requirements of large-scale photogrammetry. Ground-based pseudolites can strengthen the measurement geometry for airborne GPS systems, and improve ambiguity resolution. As a result, positioning accuracy and reliability can be improved, especially in the vertical component. In order to effectively augment DGPS aided airborne surveying with pseudolites, carrier phase measurements of pseudolites need to be employed in the positioning process. However, due to the comparatively small separations between pseudolites and receivers, some challenging issues have to be investigated, such as geometry design, nonlinearity, tropospheric delay and pseudolite location errors. Geometry design is extremely important for pseudolite augmented GPS positioning system. Optimally located pseudolite and reference receiver can significantly improve the geometric strength of positioning solutions and thus reduce the effects of nonlinearity and pseudolite location error. The optimal locations of pseudolite and reference receiver are proposed based on analyzing these issues and the simulation results in airborne surveying scenarios. Nonlinearity is a challenging issue in pseudolite augmented DGPS. The nonlinear geometry bias in processing pseudolite measurements can be effectively eliminated by Projected Single Difference strategy, which can also be used in processing GPS measurements to improve the positioning accuracy. Several pseudolite tropospheric delay models are introduced and evaluated, and optimal models corresponding to different applications are proposed. Simulation and real data test results have shown the effectiveness of the proposed methods.
Wang, Z, Huang, S & Dissanayake, G 2005, 'Decoupling Localization and Mapping in SLAM Using Compact Relative Maps', Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Edmonton, Canada, pp. 1041-1046.
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In this paper, we propose a new algorithm for SLAM that makes use of a state vector consisting of quantities that describes the relative locations among features. In contrast to previous relative map strategies, the new state vector is compact and always consists of 2n ¡ 3 elements (in a 2-D environment) where n is the number of features in the map. It is also shown that the information from observations can be transformed and grouped into two parts: first one containing the information about the map and the second one containing the information about the robot location relative to the features in the map. Therefore the SLAM can be decoupled into two processes where mapping uses the first part of the transformed observation vector and localization becomes a 3-dimensional estimation problem. It is also shown that the information matrix of the map is exactly sparse, resulting in potential computational savings when an information filter is used for mapping. The new decoupled SLAM algorithm is called D-SLAM and is illustrated using simulation.
Zhang, Z & Kodagoda, S 2005, 'A Monocular Vision Based Localizer', Proceedings of the 2005 Australasian Conference on Robotics and Automation, Australasian Conference on Robotics and Automation, Australian Robotics and Automation Association, Sydney, Australia, pp. 1-6.
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Utilization of low cost sensing is feasible in office like environments due to the regular man made structures. In this paper, we presented an algorithm, which exploits floor boundaries as a feature for robot localization. A colour based floor detection technique along with laser-like scan generation algorithm is proposed for feature extraction. Then an AMCL based localizer is used for robot localization. Experimental results in an office like environment shows the feasibility of the monocular vision based localization.
Zhang, Z & Kodagoda, S 2005, 'Multi-sensor Approach for People Detection', Proceedings of the International Conference on Intelligent Sensors, Sensor Networks and Information Processing, International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Casual Productions, Melbourne, Australia, pp. 355-360.
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Human detection is an important research topic for many researchers who are working with surveillance, safe driving, military and security applications. It is now becoming more and more appropriate with the global increase in the terrorism related activities. This paper presents an algorithm for people detection using information gathered from a composite moving sensor incorporating a camera and a laser range finder. Laser range finder is used to identify a region of interest (ROJ) where a moving object is likely to be present. Corresponding ROI in the visual image is then analyzed and a hierarchical template matching strategy is used to confirm the presence of a moving human. This approach improves the robustness of the template matching and the computational efficiency as the matching is only done in the resized ROI. The proposed strategy is evaluated through experimentation.