Ravindra Ranasinghe

University of Technology Sydney | UTS · Robotics Institute

This paper addresses the issue of monitoring spatial environmental phenomena of interest utilizing information collected by a network of mobile, wireless and noisy sensors that can take discrete measurements as they navigate through the environment. It is proposed to employ Gaussian Markov random field (GMRF) represented on an irregular discrete la...

This paper presents a novel localisation framework based on an omnidirectional camera, targeted at outdoor urban environments. Bearing only information to persistent and easily observable high-level semantic landmarks (such as lampposts , street-signs and trees) are perceived using a Convolutional Neural Network (CNN). The framework utilises an inf...

Globally, the water industry considers microbial induced corrosion of concrete sewer pipes as a serious problem. There are reported analytical models and data analytic models that are used to predict the rate of corrosion throughout the sewer network. Those models incorporate surface moisture conditions of concrete sewer pipes as observations. Due...

The main contribution of this paper is a novel extended Kalman filter (EKF) based localisation scheme that fuses two complementary approaches to outdoor vision based localisation. This EKF is aided by a front end consisting of two Convolutional Neural Networks (CNNs) that provide the necessary perceptual information from camera images. The first ap...

Globally, the water industry considers microbial induced corrosion of concrete sewer pipes as a serious problem. In order to alleviate the effects of sewer corrosion, water utilities use predictive models for estimating the rate of corrosion throughout the sewer network. Those models incorporate surface moisture conditions of the concrete sewer pip...

This paper presents a generalized multistage bayesian framework to enable an autonomous robot to complete high‐precision operations on a static target in a large field. The proposed framework consists of two multistage approaches, capable of dealing with the complexity of high‐precision operation in a large field to detect and localize the target....

This paper presents an algorithm for calibrating a “3D range sensor” constructed using a two-dimensional laser range finder (LRF), that is rotated about an axis using a motor to obtain a three-dimensional point cloud. The sensor assembly is modelled as a two degree of freedom open kinematic chain, with one joint corresponding to the axis of the int...

Sewerage systems are paramount underground infrastructure assets for any nation. In most cities, they are old and have been exposed to significant microbial induced corrosion. It is a serious global problem as they pose threats to public health and economic repercussions to water utilities. For managing sewer assets efficaciously, it is vital to pr...

In wastewater industry, real-time sensing of surface temperature variations on concrete sewer pipes is paramount in assessing the rate of microbial-induced corrosion. However, the sensing systems are prone to failures due to the aggressively corrosive environmental conditions inside sewer assets. Therefore, reliable sensing in such infrastructures...

This paper introduces the use of the vector distance function (VDF) for representing environments , particularly for the use in locali-sation algorithms. It is shown that VDF has a continuous derivative at the object boundary in contrast to unsigned distance transform, and does not require an environment populated with closed object as in the case...

This paper addresses the problem of driving robotic sensors for an energy-constrained mobile wireless network in efficiently monitoring and predicting spatial phenomena, under data locational errors. The paper first discusses how errors of mobile sensor locations affect estimating and predicting the spatial physical processes, given that spatial fi...

This paper addresses the problem of selecting the most informative sensor locations out of all possible sensing positions in predicting spatial phenomena by using a wireless sensor network. The spatial field is modeled by Gaussian Markov random fields (GMRFs), where sparsity of the precision matrix enables the network to benefit from computation. A...

In this paper, we present a novel RGB-D feature, RISAS, which is robust to Rotation, Illumination and Scale variations through fusing Appearance and Shape information. We propose a keypoint detector which is able to extract information rich regions in both appearance and shape using a novel 3D information representation method in combination with g...

The purpose of this paper is to explore how an operator's grip plays a role in physical Human Robot Interaction (pHRI). By considering how the operator reacts to or initiates changes in control, it is possible to study the operator's grip pattern. By analyzing the grip pattern, it is possible to incorporate their natural response in order to create...

The main contribution of this paper is an extended Kalman filter (EKF) based framework for mobile robot localisation in occupancy grid maps (OGMs), when the initial location is approximately known. We propose that the observation equation be formulated using the unsigned distance transform based Chamfer Distance (CD) that corresponds to a laser sca...

This paper presents a fast global scan matching technique for high-speed vehicle navigation. The proposed grid-based scan-to-map matching technique collectively handles unprocessed scan points at each grid cell as a grid feature. The grid features are transformed and located in the global frame and updated every time a new scan is acquired. Since r...

This paper presents the map-based navigation of a car with autonomous capabilities using grid-based scan-to-map matching. The autonomous car used for demonstration is built based on Toyota Prius and can control the throttle, the brake and the steering by a computer. The proposed grid-based scan-to-map matching method represents a map with a finite...

This paper presents an active object recognition and pose estimation system for household objects in a highly cluttered environment. A sparse feature model, augmented with the characteristics of features when observed from different viewpoints is used for recognition and pose estimation while a dense point cloud model is used for storing geometry....

This brief addresses the issue of monitoring physical spatial phenomena of interest using information collected by a resource-constrained network of mobile, wireless, and noisy sensors that can take discrete measurements as they navigate through the environment. We first propose an efficient novel optimality criterion for designing a sampling strat...

This paper presents a modular algorithm pipeline for recognizing textured household objects in cluttered environment and estimating 6 DOF poses using an RGB-D sensor. The method draws from recent advances in this area and introduces a number of innovations that enable improved performances and faster operational speed in comparison with the state-o...

Assistive Robotics(AR) is a rapidly expanding field, implementing advanced intelligent machines capable of working collaboratively with a range of human users; as assistants, tools and as companions. These AR devices can provide assistance to stretched carers when transferring non-ambulatory patients safely. This paper presents the preliminary outc...

This paper presents a distributed spatial estimation and prediction approach to address the centrally-computed scheme of Gaussian Process regression at each robotic sensor in resource-constrained networks of mobile, wireless and noisy agents monitoring physical phenomena of interest. A mobile sensor independently estimate its own parameters using c...

This paper proposes a data driven machine learning model for spatial prediction of hydrogen sulfide (H2S) in a gravity sewer system. The gaseous H2S in the overhead of the gravity sewer is modelled using a Gaussian Process with a new covariance function due to constraints of sewer boundaries. The covariance function is proposed based on the distanc...

This paper presents a co-design process and an assisted navigation strategy that enables a novel assistive robot, Smart Hoist, to aid carers transferring non-ambulatory residents. Smart Hoist was co-designed with residents and carers at IRT Woonona residential care facility to ensure that the device can coexist in the facility, while providing assi...

This paper addresses the issue of monitoring physical spatial phenomena of interest utilizing the information collected by a network of mobile, wireless and noisy sensors that can take discrete measurements as they navigate through the environment. The spatial phenomenon is statistically modelled by a Gaussian Markov Random Field (GMRF) with hyperp...

In this paper, the problem of localising a robot within a known two-dimensional environment is formulated as one of minimising the Chamfer Distance between the corresponding occupancy grid map and information gathered from a sensor such as a laser range finder. It is shown that this nonlinear optimisation problem can be solved efficiently and that...

This paper addresses the sensor placement problem associated with monitoring spatial phenomena, where mobile sensors are located on the optimal sampling paths yielding a lower prediction error. It is proposed that the spatial phenomenon to be monitored is modeled using a Gaussian Process and a variance based density function is employed to develop...

This paper addresses the trade-off between the sensing quality and the energy consumption in the wireless sensor network associated with monitoring spatial phenomena. We use a non-parametric Gaussian Process to model the spatial phenomena to be monitored and simulated annealing based approximately heuristic algorithm for sensor selection. Our novel...

This paper addresses the sensor selection problem associated with monitoring spatial phenomena, where a subset of k sensor measurements from among a set of n potential sensor measurements is to be chosen such that the root mean square prediction error is minimised. It is proposed that the spatial phenomena to be monitored is modelled using a Gaussi...

For road vehicles, knowledge of terrain types is useful in improving passenger safety and comfort. The conventional methods are susceptible to vehicle speed variations and in this paper we present a method of using Laser Measurement System (LMS) data for speed independent road type classification. Experiments were carried out with an instrumented r...

Simultaneous Localization and Mapping (SLAM) problem has been an active area of research in robotics for more than a decade. Many fundamental and practical aspects of SLAM have been addressed and some impressive practical solutions have been demonstrated. The aim of this paper is to provide a review of the current state of the research on feature b...

A representation of space that includes both geometric and semantic information enables a robot to perform high-level tasks in complex environments. Identifying and categorizing environments based on onboard sensors are essential in these scenarios. The Kinect™, a 3D low cost sensor is appealing in these scenarios as it can provide rich information...

Transmitting variable-bit-rate real-time data on the uplink of a polled wireless local area network requires careful scheduling to achieve satisfactory performance and capacity. This is a ``blind'' scheduling problem, since the number and arrival times of packets at each remote station are not known by the scheduler. Embedded round robin (ERR) was...

Wireless local area networks have developed into a promising solution to support advanced data services in untethered environments. Selection of an efficient packet-scheduling scheme is important for managing the bandwidth while satisfying QoS requirements of active sessions having diverse traffic characteristics. The key difficulty is the distribu...

Wireless local area networks are a viable technology to support multimedia traffic One of the prominent wireless local area network standards is the IEEE 802.11 standard. In wireless multimedia networks, mobile stations will be capable of generating a heterogeneous traffic mix with varying bandwidth requirements. In this paper, we investigate in de...

Wireless local area networks are a promising solution to support advanced data services in mobile environments. The IEEE 802.11 wireless LAN standard is emerging as a mature technology to support delay sensitive network services. In order to support these services the standard has proposed the use of a polling scheme; however, existing polling sche...

Wireless local area networks are a viable technology to support multimedia traffic. One of the prominent wireless local area network standards being adopted as a mature technology is the IEEE 802.11 standard. In wireless multimedia networks, mobile stations will be capable of generating a heterogeneous traffic mix and therefore it is crucial to dev...