Publications

Kim, J, Sukkarieh, S & Wishart, S 2006, 'Springer Tracts in Advanced Robotics'.

Wang, Z, Huang, S & Dissanayake, G 2006, 'Implementation Issues and Experimental Evaluation of D-SLAM' in Corke, P & Sukkarieh, S (eds), Field and Service Robotics, Springer-Verlag, Berlin, Heidelberg, pp. 155-166.

Ha, QP & Dissanayake, G 2006, 'Robust Formation Using Reactive Variable Structure Systems', International Transactions on Systems Science and Applications, vol. 1, no. 2, pp. 181-189.

Kecskeméthy, A, Waldron, K, Parenti-Castelli, V & Ceccarelli, M 2006, 'Mechanism and Machine Theory: Editorial', Mechanism and Machine Theory, vol. 41, no. 1, p. 1.
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Kim, J, Ong, LLS, Nettleton, E & Sukkarieh, S 2006, 'Decentralised approach to UAV navigation: without the use of GPS and preloaded maps', Proceedings of the Institution of Mechanical Engineers, vol. 218, pp. 399-416.

Kirchner, NG, Paul, G & Liu, D 2006, 'Bridge Maintenance Robotic Arm: Mechanical Technique to reduce the nozzle Force of a Sandblasting Rig', Journal of Wuhan University of Technology, vol. 28, no. 164, pp. 12-18.

Kodagoda, S, Wijesoma, WS & Balasuriya, A 2006, 'CuTE: Curb Tracking and Estimation', The IEEE Transaction on Control Systems Technology, vol. 14, no. 5, pp. 951-957.
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The number of road accident related fatalities and damages are reduced substantially by improving road infrastructure and enacting and imposing laws. Further reduction is possible through embedding intelligence onto the vehicles for safe decision making. Road boundary information plays a major role in developing such intelligent vehicles. A prominent feature of roads in urban, semi-urban, and similar environments, is curbs on either side defining the road's boundary. In this brief, a novel methodology of tracking curbs is proposed. The problem of tracking a curb from a moving vehicle is formulated as tracking of a maneuvering target in clutter from a mobile platform using onboard sensors. A curb segment is presumed to be the maneuvering target, and is modeled as a nonlinear Markov switching process. The target's (curb's) orientation and location measurements are simultaneously obtained using a two-dimensional (2-D) scanning laser radar (LADAR) and a charge-coupled device (CCD) monocular camera, and are modeled as traditional base state observations. Camera images are also used to estimate the target's mode, which is modeled as a discrete-time point process. An effective curb tracking algorithm, known as Curb Tracking and Estimation (CuTE) using multiple modal sensor information is, thus, synthesized in an image enhanced interactive multiple model filtering framework. The use and fusion of camera vision and LADAR within this frame provide for efficient, effective, and robust tracking of curbs. Extensive experiments conducted in a campus road network demonstrate the viability, effectiveness, and robustness of the proposed method

Kwok, N, Liu, D & Dissanayake, G 2006, 'Evolutionary Computing Based Mobile Robot Localization', Engineering Applications of Artificial Intelligence, vol. 19, no. 8, pp. 857-868.
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Evolutionary computing techniques, including genetic algorithms (GA), particle swarm optimization (PSO) and ants system (AS) are applied to the localization problem of a mobile robot. Salient features of robot localization are that the system is partially dynamic and information for fitness evaluation is incomplete and corrupted by noise. In this research, variations to the above three evolutionary computing techniques are proposed to tackle the specific dynamic and noisy system. Their performances are compared based on simulation and experiment results and the feasibility of the proposed approach to mobile robot localization is demonstrated.

Leung, C, Huang, S, Kwok, N & Dissanayake, G 2006, 'Planning under Uncertainty Using Model Predictive Control for Information Gathering', Robotics and Autonomous Systems, vol. 54, no. 11, pp. 898-910.
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This paper considers trajectory planning problems for autonomous robots in information gathering tasks. The objective of the planning is to maximize the information gathered within a finite time horizon. It is assumed that either the Extended Kalman Filter (EKF) or the Extended Information Filter (EIF) is applied to estimate the features of interest and the information gathered is expressed by the covariance matrix, or information matrix. It is shown that the planning process can be formulated as an optimal control problem for a nonlinear control system with a gradually identified model. This naturally leads to the Model Predictive Control (MPC) planning strategy, which uses the updated knowledge about the model to solve a finite horizon optimal control problem at each time step and only executes the first control action. The proposed MPC framework is demonstrated through solutions to two challenging information gathering tasks: (1) Simultaneous planning, localization, and map building (SPLAM) and (2) Multi-robot Geolocation. It is shown that MPC can effectively deal with dynamic constraints, multiple robots/features and a range of objective functions.

Liu, D, Wu, X, Paul, G & Dissanayake, G 2006, 'Case Studies on an Approach to Multiple Autonomous Vehicle Motion Coordination', Journal of Wuhan University of Technology, vol. 26, no. 164, pp. 26-31.

Rekleitis, I, Meger, D & Dudek, G 2006, 'Simultaneous planning, localization, and mapping in a camera sensor network', ROBOTICS AND AUTONOMOUS SYSTEMS, vol. 54, no. 11, pp. 921-932.
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Alempijevic, A, Kodagoda, S, Underwood, J, Kumar, S & Dissanayake, G 2006, 'Mutual Information Based Sensor Registration and Calibration', Proceedings of the 2006 IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Beijing, China, pp. 25-30.
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Knowledge of calibration, that defines the location of sensors relative to each other, and registration, that relates sensor response due to the same physical phenomena, are essential in order to be able to fuse information from multiple sensors. In this paper, a mutual information (MI) based approach for automatic sensor registration and calibration is presented. Unsupervised learning of a nonparametric sensing model by maximizing mutual information between signal streams is used to relate information from different sensors, allowing unknown sensor registration and calibration to be determined. Experiments conducted in an office environment are used to illustrate the effectiveness of the proposed technique. Two laser sensors are used to capture people mobbing in an arbitrarily manner in the environment and MI from a number of attributes of the motion are used for relating the signal streams from the sensors. Thus the sensor registration and calibration is achieved without using artificial patterns or pre-specified motions

Butler, Z & Fitch, R 2006, 'Internally specified heterogeneous self-reconfiguration', 3rd Conference on Foundations of Nanoscience: Self-Assembled Architectures and Devices, FNANO 2006, pp. 196-202.
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Self-reconfiguring robots are systems built from a large number of modules (which can be homogeneous or heterogeneous) that have the ability to change shape to fit the task at hand. Previous algorithms for shape formation have generally used a data structure common to all modules and passed in from an external user. In this work, we show how some of our previous algorithms can be easily adapted to an on-demand situation, so that the system can form the correct (heterogeneous) shape with a small amount of communication and state. We can also use this adapted algorithm to generate locomotion among the modules with little additional overhead.© 2006 by ScienceTechnica, Inc.

Cheong, C, Tan, K, Liu, D & Xu, J 2006, 'A Multiobjective Evolutionary Algorithm for Solving Vehicle Routing Problem with Stochastic Demand', Proceedings of 2006 IEEE Congress on Evolutionary Computation, IEEE Congress on Evolutionary Computation, IEEE, Vancouver, Canada, pp. 5519-5526.
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This paper considers the routing of vehicles with limited capacity from a central depot to a set of geographically dispersed customers where actual demand is revealed only when the vehicle arrives at the customer. The solution to this vehicle routing problem with stochastic demand (VRPSD) involves the optimization of complete routing schedules with minimum travel distance, driver remuneration, and number of vehicles, subject to a number of constraints such as vehicle time window and capacity. To solve such a multiobjective combinatorial optimization problem, this paper presents a multiobjective evolutionary algorithm that incorporates two VRPSD-specific heuristics for local exploitation and a route simulation method to evaluate the fitness of solutions. A novel way of assessing the quality of solutions to the VRPSD on top of comparing their expected costs is also proposed. It is shown that the algorithm is capable of finding useful tradeoff solutions which are robust to the stochastic nature of the problem.

Cheong, CY, Tan, KC, Liu, DK & Xu, JX 2006, 'A multiobjective evolutionary algorithm for solving vehicle routing problem with stochastic demand', 2006 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-6, IEEE Congress on Evolutionary Computation, IEEE, Vancouver, CANADA, pp. 1355-+.

Dissanayake, G, Paxman, J, Miro, JV, Thane, O & Thi, H-T 2006, 'Robotics for urban search and rescue', 2006 INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS, VOLS 1 AND 2, International Conference on Industrial and Information Systems, IEEE, Peradeniya, SRI LANKA, pp. 294-+.
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Dissanayake, G, Paxman, JP, Valls Miro, J, Thane, O & Thi, H 2006, 'Robotics for urban search and rescue', Proceedings of the IEEE First International Conference on Industrial and Information Systems (ICIIS2006), IEEE International Conference on Industrial and Information Systems, IEEE, Peradeniya, Sri Lanka, pp. 294-298.
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This paper describes a team of robots that are designed for urban search and rescue applications. The team CASualty consists of four tele-operated robots and one autonomous robot. A brief description of the capabilities of the robot team is presented together with the details of capabilities of the autonomous robot HOMER. In particular, the software architecture, user interface, strategies used for mapping, exploration and the identification of human victims present in the environment are described. The team participated in an international competition on urban search and rescue (RoboCup Rescue) held in Bremen, Germany in June 2006 where HOMER was placed second in the autonomy challenge

Ellekilde, L, Valls Miro, J & Dissanayake, G 2006, 'Fusing range and intensity images for generating dense models of three-dimensional environments', Proceedings of the 2006 IEEE International Conference on Man-Machine Systems (ICoMMS 2006), IEEE International Conference on Man-Machine Systems, IET, Langkawi, Malaysia, pp. 1-5.

Enedah, CC & Waldron, K 2006, 'Robotic Perception of Mechanical Properties of the Human Skin: A Validation Study', Medicine Meets Virtual Reality 14, Medicine Meets Virtual Reality, Long Beach, CA.

Estremera, J & Waldron, K 2006, 'Leg Thrust Control for Stabilization of Dynamic Gaits in a Quadruped Robot', Proceedings of ROMANSY 2006, Warsaw, Poland, pp. 213-220.

Ha, QP, Ha, H & Dissanayake, G 2006, 'Robotic formation control using variable structure systems approach', Dis 2006: Ieee Workshop On Distributed Intelligent Systems: Collective Intelligence And Its Applications, Proceedings, IEEE Workshop on Distributed Intelligent Systems, IEEE Computer Soc, Prague, CZECH REPUBLIC, pp. 37-42.
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This paper addresses robust control of multiple mobile robots moving in desired formations. A rigorous control technique for such an agent-based robotic system may encounter problems of singularity, parameter sensitivity and inter-robot collision. Our pr

Herath, DC, Kodagoda, KRS & Dissanayake, G 2006, 'Modeling errors in small baseline stereo for SLAM', 2006 9TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION, VOLS 1- 5, 9th International Conference on Control, Automation, Robotics and Vision, IEEE, Singapore, SINGAPORE, pp. 2034-+.

Herath, HD, Kodagoda, S & Dissanayake, G 2006, 'Modelling Errors in Small Baseline Stereo for SLAM', Proceedings of the 9th International Conference on Control, Automation, Robotics and Vision, International Conference on Control, Automation, Robotics and Vision, IEEE, Singapore, pp. 836-841.
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In the past few years, there has been significant advancement in localization and mapping using stereo cameras. Despite the recent successes, reliably generating an accurate geometric map of a large indoor area using stereo vision still poses significant challenges due to the accuracy and reliability of depth information especially with small baselines. Most stereo vision based applications presented to date have used medium to large baseline stereo cameras with Gaussian error models. Here we make an attempt to analyze the significance of errors in small baseline (usually <0.1m) stereo cameras and the validity of the Gaussian assumption used in the implementation of Kalman filter based SLAM algorithms. Sensor errors are analyzed through experimentations carried out in the form of a robotic mapping. Then we show that SLAM solutions based on the extended Kalman filter (EKF) could become inconsistent due to the nature of the observation models used

Herath, HD, Kodagoda, S & Dissanayake, G 2006, 'Simultaneous Localisation and Mapping: A Stereo Vision Based Approach', Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Beijing, China, pp. 922-927.
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With limited dynamic range and poor noise performance, cameras still pose considerable challenges in the application of range sensors in the context of robotic navigation, especially in the implementation of simultaneous localisation and mapping (SLAM) with sparse features. This paper presents a combination of methods in solving the SLAM problem in a constricted indoor environment using small baseline stereo vision. Main contributions include a feature selection and tracking algorithm, a stereo noise filter, a robust feature validation algorithm and a multiple hypotheses adaptive window positioning method in 'closing the loop'. These methods take a novel approach in that information from the image processing and robotic navigation domains are used in tandem to augment each other. Experimental results including a real-time implementation in an office-like environment are also presented

Huang, S & Dissanayake, G 2006, 'Convergence Analysis for Extended Kalman Filter based SLAM', Proceedings of the 2006 IEEE International Conference on Robotics and Automation, IEEE International Conference on Robots and Automation, IEEE, Orlando, USA, pp. 412-417.
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The main contribution of this paper is a theoretical analysis of the extended Kalman filter (EKF) based solution to the simultaneous localisation and mapping (SLAM) problem. The convergence properties for the general nonlinear two-dimensional SLAM are provided. The proofs clearly show that the robot orientation error has a significant effect on the limit and/or the lower bound of the uncertainty of the landmark location estimates. Furthermore, some insights to the performance of EKF SLAM and a theoretical analysis on the inconsistencies in EKF SLAM that have been recently observed are given

Huang, S, Wang, ZZ & Dissanayake, G 2006, 'Mapping large scale environments using relative position information among landmarks', Proceedings of the 2006 IEEE International Conference on Robotics and Automation, IEEE International Conference on Robots and Automation, IEEE, Orlando, FL, pp. 2297-2302.
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The main contribution of this paper is a new SLAM algorithm for the mapping of large scale environments by combining local maps. The local maps can be generated by traditional Extended Kalman Filter (EKF) based SLAM. Relationships between the locations o

Kim, J & Sukkarieh, S 2006, 'Robust multi-loop airborne SLAM in unknown wind environments', Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on, IEEE, pp. 1536-1541.

Kirchner, NG, Liu, D & Dissanayake, G 2006, 'Bridge Maintenance Robotic Arm: Capacitive Sensor for Obstacle Ranging in Particle Laden Air', Proceedings of the 23rd International Symposium on Automation and Robotics in Construction, International Symposium of Automation and Robotics in Construction, Japan Robot Association, Tokyo, Japan, pp. 596-601.

Kodagoda, KRS, Alempijevic, A, Underwood, J, Kumar, S & Dissanayake, G 2006, 'Sensor registration and calibration using moving targets', 2006 9TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION, VOLS 1- 5, 9th International Conference on Control, Automation, Robotics and Vision, IEEE, Singapore, SINGAPORE, pp. 1992-+.

Kodagoda, S, Alempijevic, A, Underwood, J, Kumar, S & Dissanayake, G 2006, 'Sensor Registration and Calibration Using Moving Targets', Proceedings of the 9th International Conference on Control, Automation, Robotics and Vision, International Conference on Control, Automation, Robotics and Vision, IEEE, Singapore, pp. 830-835.
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Multimodal sensor registration and calibration are crucially important aspects in distributed sensor fusion. Unknown relationships of sensors and joint probability distribution between sensory signals make the sensor fusion nontrivial. In this paper, we adopt a Mutual Information (MI) based approach for sensor registration and calibration. It is based on unsupervised learning of a nonparametric sensing model by maximizing mutual information between signal streams. Experiments were carried out in an office like environment with two laser sensors capturing arbitrarily moving people. Attributes of the moving targets are used. Problems due to target occlusions are alleviated by the multiple model tracker. The registration and calibration methodology does not require any artificially generated patterns or motions unlike other calibration methodologies

Kulatunga, AK, Liu, D, Dissanayake, G & Siyambalapitiya, SB 2006, 'Ant Colony Optimization based Simultaneous Task Allocation and Path Planning of Autonomous Vehicles', Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems, IEEE International Conference on Cybernetics and Intelligent Systems, IEEE, Bangkok, Thailand, pp. 823-828.
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This paper applies a meta-heuristic based ant colony optimization (ACO) technique for simultaneous task allocation and path planning of automated guided vehicles (AGV) in material handling. ACO algorithm allocates tasks to AGVs based on collision free path obtained by a proposed path and motion planning algorithm. The validity of this approach is investigated by applying it to different task and AGV combinations which have different initial settings. For small combinations, i.e. small number of tasks and vehicles, the quality of the ACO solution is compared against the optimal results obtained from exhaustive search mechanism. This approach has shown near optimal results. For larger combinations, ACO solutions are compared with simulated annealing algorithm which is another commonly used meta-heuristic approach. The results show that ACO solutions have slightly better performance than that of simulated annealing algorithm

Kulatunga, AK, Liu, DK, Dissanayake, G & Siyambalapitiya, SB 2006, 'Ant colony optimization based simultaneous task allocation and path planning of autonomous vehicles', 2006 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2, IEEE Conference on Cybernetics and Intelligent Systems, IEEE, Bangkok, THAILAND, pp. 727-+.

Kwok, N, Ha, QP, Liu, D & Fang, G 2006, 'Intensity-Preserving Contrast Enhancement for Gray Level Images Using Multi-Objective Particle Swarm Optimisation', Proceedings of the 2006 IEEE Conference on Automation Science and Engineering, IEEE Conference on Automation Science and Engineering, IEEE, Shanghai, China, pp. 19-24.
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This paper addresses the enhancement of the contrast of gray-level digital images while preserving the mean image intensity, thus, providing better viewing consistency and effectiveness. The contrast enhancement is achieved by maximizing the information content carried in the image with a continuous intensity transform function and the mean image intensity is preserved, by using the gamma-correction approach. Since the contrast enhancement and intensity preservation are contradicting, a multi-objective particle swarm optimization (MPSO) algorithm is developed to resolve this trade-off. Benchmark images, street senses and skyline images are included to illustrate the effectiveness of the proposed approach

Kwok, N, Liu, D, Tan, K & Ha, QP 2006, 'An Empirical Study on the Settings of Control Coefficients in Particle Swarm Optimization', Proceedings of the 2006 IEEE Congress on Evolutionary Computation, IEEE Congress on Evolutionary Computation, IEEE, Vancouver BC, Canada, pp. 3165-3172.
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The effects of randomness of control coefficients in particle swarm optimization (PSO) are investigated through empirical studies. The PSO is viewed as a method to solve a coverage problem in the solution space when the global-best particle is reported as the solution. Randomness of the control coefficients, therefore, plays a crucial role in providing an efficient and effective algorithm. Comparisons of performances are made between the uniform and Gaussian distributed random coefficients in adjusting particle velocities. Alternative strategies are also tested, they include: i) pre-assigned randomness through the iterations, ii) selective hybrid random adjustment based on the fitness of the particles. Furthermore, the effect of velocity momentum factor is compared between a constant and random momentum. Numerical results show that performances of the proposed variations are comparable to the conventional implementation for simple test functions. However, enhanced performances using the selective and hybrid strategy are observed for complicate functions.

Kwok, NM, Liu, DK, Tan, KC & Ha, QP 2006, 'An empirical study on the settings of control coefficients in particle swarm optimization', 2006 IEEE Congress on Evolutionary Computation, CEC 2006, pp. 823-830.
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The effects of randomness of control coefficients in Particle Swarm Optimization (PSO) are investigated through empirical studies. The PSO is viewed as a method to solve a coverage problem in the solution space when the global-best particle is reported as the solution. Randomness of the control coefficients, therefore, plays a crucial role in providing an efficient and effective algorithm. Comparisons of performances are made between the uniform and Gaussian distributed random coefficients in adjusting particle velocities. Alternative strategies are also tested, they include: i) pre-assigned randomness through the iterations, ii) selective hybrid random adjustment based on the fitness of the particles. Furthermore, the effect of velocity momentum factor is compared between a constant and random momentum. Numerical results show that performances of the proposed variations are comparable to the conventional implementation for simple test functions. However, enhanced performances using the selective and hybrid strategy are observed for complicate functions. ©2006 IEEE.

Lau, H, Huang, S & Dissanayake, G 2006, 'Probabilistic Search for a Moving Target in an Indoor Environment', 2006 IEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Beijing, China, pp. 3393-3398.
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We consider a search for a target moving within a known indoor environment partitioned into interconnected regions of varying sizes. The knowledge of target location is described as a probability distribution over the regions, and the searcher can only move from one region to another as the structure allows. The objective is to find a feasible path through the regions that maximizes the probability of locating the target within fixed time. This problem generalizes the existing optimal searcher path problem (OSP) by additionally stipulating a minimum amount of time that a finite-speed searcher must spend to travel through a region before reaching the next. We propose a technique to obtain the upper bound of detection for solving the problem in a branch and bound framework. Comparisons show that the technique is also superior to known bounding methods for the original optimal searcher path problem

Leung, C, Huang, S & Dissanayake, G 2006, 'Active SLAM Using Model Predictive Control and Attractor Based Exploration', 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Beijing, China, pp. 5026-5031.
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Active SLAM poses the challenge for an autonomous robot to plan efficient paths simultaneous to the SLAM process. The uncertainties of the robot, map and sensor measurements, and the dynamic and motion constraints need to be considered in the planning process. In this paper, the active SLAM problem is formulated as an optimal trajectory planning problem. A novel technique is introduced that utilises an attractor combined with local planning strategies such as model predictive control (a.k.a. receding horizon) to solve this problem. An attractor provides high level task intentions and incorporates global information about the environment for the local planner, thereby eliminating the need for costly global planning with longer horizons. It is demonstrated that trajectory planning with an attractor results in improved performance over systems that have local planning alone

Liu, D, Wang, D & Dissanayake, G 2006, 'A Force field Method Based Multi Robot Collaboration', Proceedings of IEEE Conference on Robotics, Automation and Mechatronics, 2006, IEEE Conference on Robotics, Automation and Mechatronics, IEEE, Bangkok, Thailand, pp. 662-667.
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A force field (F2) based multi-robot collaboration method is presented in this paper. In this method, a virtual force field is generated for every moving robot and continuously changing based on the robot status including its traveling speed, dimension, priority, location and environment, etc. The interactions among robots' force fields and obstacles provide a natural way for collision avoidance and collaboration while robots are on their way to goals. In this paper, the definition of reaction force direction is modified to reduce robot orientation oscillations which occur when a robot approaches obstacles or other robots. Then the influence of task priority on motion planning and the problem of deadlock in multi-robot cases are discussed. Simulations in a real indoor environment were carried out and demonstrated the feasibility and effectiveness of this method

Liu, D, Wu, X, Kulatunga, AK & Dissanayake, G 2006, 'Motion Coordination of Multiple Autonomous Vehicles in Dynamic and Strictly Constrained Environments', Proceedings of the IEEE Conference on Cybernetics and Intelligent Systems, IEEE International Conference on Cybernetics and Intelligent Systems, IEEE, Bangkok, Thailand, pp. 204-209.
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With the increasing applications of fully autonomous vehicles, efficient motion coordination of multi-autonomous vehicles becomes a very important problem as it significantly affects the productivity. This problem is even harder to solve with the increases of the number of autonomous vehicles employed in a dynamic changing environment and constraints to vehicle movement. This paper presents a simultaneous path and motion planning (SiPaMoP) approach to coordinate motions of multi-autonomous vehicles in dynamic and strictly constrained environments. This approach integrates the path planning, collision avoidance and motion planning into a comprehensive model, which has so far not attracted a lot of attention in the academic literature, and optimizes vehicles' path and speed to minimize the completion time of a set of tasks. Simulation results demonstrated that this approach can effectively coordinate the motion of a team of vehicles, and solve the problems of traffic congestion and collision under various traffic conditions

Liu, DK, Wang, D & Dissanayake, G 2006, 'A force field method based multi-robot collaboration', 2006 IEEE CONFERENCE ON ROBOTICS, AUTOMATION AND MECHATRONICS, VOLS 1 AND 2, IEEE Conference on Robotics, Automation and Mechatronics, IEEE, Bangkok, THAILAND, pp. 511-+.

Liu, DK, Wu, X, Kulatunga, AK & Dissanayake, G 2006, 'Motion coordination of multiple autonomous vehicles in dynamic and strictly constrained environments', 2006 IEEE CONFERENCE ON CYBERNETICS AND INTELLIGENT SYSTEMS, VOLS 1 AND 2, IEEE Conference on Cybernetics and Intelligent Systems, IEEE, Bangkok, THAILAND, pp. 683-+.

McIntyre, DG, Liu, DK, Lasky, VL & Murray, SJ 2006, 'A remote water-level rig laboratory for e-learning', 2006 7TH INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY BASED HIGHER EDUCATION AND TRAINING, VOLS 1 AND 2, 7th International Conference on Information Technology Based Higher Education and Training, IEEE, Sydney, AUSTRALIA, pp. 77-81.
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Paul, G & Liu, D 2006, 'Replanning of Multiple Autonomous Vehicles in Material Handling', 2006 IEEE Conference on Robotics, Automation and Mechatronics, IEEE Conference on Robotics, Automation and Mechatronics, IEEE, Bangkok, Thailand, pp. 1-6.
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The fully automated docks in Australia present opportunities for applications of autonomous vehicles and engineering innovation. When planning tasks to be done by multi-autonomous vehicles in an enclosed area with a known dynamic map (i.e. bi-directional path network), there are many issues that have not yet been comprehensively solved. The real world presents more complexity than the initial algorithms addressed. There are problems that occur due to interaction with the real-world. This means autonomous vehicles can stop, are affected, or face problems, and hence tasks and vehicles' paths and motion need to be replanned. In order to replan, a greater understanding of the state of vehicles, the state of the map, and importantly the importance of tasks and vehicles is definitely needed. This paper explores the improvements made to replanning by gaining a thorough understanding of the map and then utilising map information to make the best, most efficient replanning decision. Five replanning methods are investigated and four options which combine the methods in different ways are tested in this research. A map analysis method is also presented. Simulation studies show that map information based replanning is the most efficient method out of those tested

Singh, SP & Waldron, K 2006, 'Towards High-Fidelity On-Board Attitude Estimation for Legged Locomotion via a Hybrid Range and Inertial Approach', Springer Tracts in Advanced Robotics: Experimaental Robots IX, International Symposium On Experimental Robots, Springer, Springer Berlin / Heidelberg, pp. 589-598.
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Legged robots display a characteristically periodic motion. Measuring and tracking this motion has traditionally been performed using general inertial measurement techniques. While widely applied in robotics, this approach is limited in dynamic legged locomotion due to the excessive accumulation of drift from severe impact shocks (nearly 9 g in single leg experiments). This paper introduces the attitude estimation problem for legged locomotion and shows preliminary results from a more powerful combined range and inertial sensing approach. Based on a modified Extended Kalman Filter the method uses ground-directed range sensors, the stride period, and other periodic features of legged locomotion in order to address inertial drift. Together this provides rapid, robust estimates of flight phases and attitude necessary for extended dynamic legged operations.

Singh, SP, Csonka, PJ & Waldron, K 2006, 'Optical Flow Aided Motion Estimation for Legged Locomotion', Proceedings Of the International Conference on Intelligent Robots and Systems, IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Beijing, China, pp. 1738-1743.
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Dynamic legged locomotion entails navigating terrain at high speed. The impact shocks from rapid footfalls, pivotal for such mobility, introduce large impulses that saturate motion measurement. A biomimetic approach is presented in which visual information, in the form of optical flow, complements information from inertial sensors. The motion is then determined using a two-phase Hybrid Extended Kalman Filter. Experimentation in determining attitudes on a robotic leg platform shows a reduction in drift over inertial approaches and in delay over visual approaches. In tests with 6g impulses, pose was recovered within 5 deg rms with angular rate errors limited to 10 deglsec at frequencies up to 250 Hz.

Taha, T, Miro, JV & Liu, D 2006, 'An efficient path planner for large mobile platforms in cluttered environments', 2006 IEEE CONFERENCE ON ROBOTICS, AUTOMATION AND MECHATRONICS, VOLS 1 AND 2, IEEE Conference on Robotics, Automation and Mechatronics, IEEE, Bangkok, THAILAND, pp. 671-+.

Taha, T, Valls Miro, J & Dissanayake, G 2006, 'Sampling based time efficient path planning algorithm for mobile platforms', Proceeding of the 2006 IEEE International Conference on Man-Machine Systems (ICoMMS 2006), IEEE International Conference on Man-Machine Systems, IET, Langkawi, Malaysia, pp. 1-6.

Taha, T, Valls Miro, J & Liu, D 2007, 'An efficient path planner for large mobile platforms in cluttered enviornments', Proceedings of the 2006 IEEE International Conference on Robotics, Automation Mechatronics (RAM), IEEE Conference on Robotics, Automation and Mechatronics, IEEE, Bangkok, Thailand, pp. 225-230.
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This paper presents a one step smooth and efficient path planning algorithm for navigating a large robotic platform in known cluttered environments. The proposed strategy, based on the generation of a novel search space, relies on non-uniform density sampling of the free areas to direct the computational resources to troubled and difficult regions, such as narrow passages, leaving the larger open spaces sparsely populated. A smoothing penalty is also associated to the nodes to encourage the generation of gentle paths along the middle of the empty spaces. Collision detection is carried out off-line during the creation of the configuration space to speed up the actual search for the path, which is done on-line. Results prove that the proposed approach considerably reduces the search space in a meaningful and practical manner, improving the computational cost of generating a path optimised for fine and smooth motion

Takezawa, S, Ishimoto, T & Dissanayake, G 2006, 'Optimal control for simultaneous localisation and mapping problems in indoor environments with stereo vision', IECON 2006 - 32ND ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS, VOLS 1-11, 32nd Annual Conference of the IEEE-Industrial-Electronics-Society, IEEE, Paris, FRANCE, pp. 5094-+.

Takezawa, S, Ishimoto, T & Dissanayake, G 2006, 'Optimal control for simultaneous localisation and mapping problems in indoor environments with stereo vision', IECON Proceedings (Industrial Electronics Conference), pp. 4749-4754.
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This paper proposes a optimal control method for simultaneous localisation and mapping (SLAM) in an indoor environment using stereo vision. Specially designed artificial landmarks distributed in the environment are observed and extracted from a camera image. The disparity map obtained from the stereo vision system is used to obtain the ranges to these landmarks. The main contribution of the paper is the formulation of the mathematical framework for SLAM for a robot moving on a planar surface among landmarks distributed in three dimensional space. The paper also presents the results of experiments for optimal control conducted using a Pioneer robot and a Triclops stereo vision system. It is demonstrated that accurate robot and feature locations can be obtained using the proposed technique. © 2006 IEEE.

Valls Miro, J, Zhou, W & Dissanayake, G 2006, 'Towards Vision Based Navigation in Large Indoor Environments', Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2006), IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, Beijing, China, pp. 2096-2102.
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The main contribution of this paper is a novel stereo-based algorithm which serves as a tool to examine the viability of stereo vision solutions to the simultaneous localisation and mapping (SLAM) for large indoor environments. Using features extracted from the scale invariant feature transform (SIFT) and depth maps from a small vision system (SVS) stereo head, an extended Kalman filter (EKF) based SLAM algorithm, that allows the independent use of information relating to depth and bearing, is developed. By means of a map pruning strategy for managing the computational cost, it is demonstrated that statistically consistent location estimates can be generated for a small (6 m times 6 m) structured office environment, and in a robotics search and rescue arena of similar size. It is shown that in a larger office environment, the proposed algorithm generates location estimates which are topologically correct, but statistically inconsistent. A discussion on the possible reasons for the inconsistency is presented. The paper highlights that, despite recent advances, building accurate geometric maps of large environments with vision only sensing is still a challenging task

Vertechy, R, Castelli, VP & Waldron, K 2006, 'On the Driving Circuits of Electro-Sensitive Elastomers', Proceedings of Actuator 2006, Actuator 2006, Actuator 2006, Bremen, Germany, pp. 1-4.
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In the last decade, Electro-Sensitive Elastomers (ESE) with significant electro-mechanical response have been discovered. These polymers are the candidate materials for the construction of solid-state actuators and sensors. To date, devices made by ESE show performances rather below expectations. This paper addresses the dynamic performance of ESE. Experimental and simulation results are presented which show that the response of ESE can be enhanced if they are activated by proper energy sources and strategies. In particular, better results are achieved by overdriving the ESE by a capacitor charging pulsed power source.

Vidal Calleja, TA, Davison, A, Andrade-cetto, J & Murray, D 2006, 'Active Control For Single Camera Slam', 2006 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), VOLS 1-10, IEEE International Conference on Robotics and Automation (ICRA), IEEE, Orlando, FL, pp. 1930-1936.
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In this paper we consider a single hand-held camera performing SLAM at video rate with generic 6DOF motion. The aim is to optimise both the localisation of the sensor and building of the feature map by computing the most appropriate control actions or mo

Wang, D, Liu, D & Dissanayake, G 2006, 'A Variable Speed Force Field Method for Multi-Robot Collaboration', Proceedings of the IEEE/RSJ International Conference on Robots and Intelligent Systems, 2006, IEEE/RSJ International Conference on Robots and Intelligent Systems, IEEE, Beijing, China, pp. 2697-2702.

Wang, JJ, Wang, J, Sinclair, D & Watts, L 2006, 'High-Accuracy Airborne GPS/INS Positioning Augmented by Pseudolite', PROCEEDINGS OF THE 2006 NATIONAL TECHNICAL MEETING OF THE INSTITUTE OF NAVIGATION - NTM 2006, 2006 National Technical Meeting of the Institute-of-Navigation, INST NAVIGATION, Monterey, CA, pp. 515-522.

Wang, ZZ, Huang, S & Dissanayake, G 2005, 'Implementation issues and experimental evaluation of D-SLAM', Field And Service Robotics, International Conference on Field and Service Robotics, Springer-Verlag Berlin, Port Douglas, Australia, pp. 155-166.
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D-SLAM algorithm first described in [1] allows SLAM to be decoupled into solving a non-linear static estimation problem for mapping and a three-dimensional estimation problem for localization. This paper presents a new version of the D-SLAM algorithm tha