Department Publications

This paper describes the development of a quadrotor fixed-wing hybrid unmanned aerial vehicle (UAV). By combining the flying qualities of quadrotor UAV and that of fixed-wing UAVs it is possible to achieve superior flying qualities. This way, the vertical take-off and landing capability of quadrotors and the long endurance of fixed-wing UAVs have been put together, while eliminating the disadvantages of both of these UAV types. The proposed hybrid drone has shown exciting performance in taking-off, cruising and landing fully autonomously. Control transition from quadrotor to fixed-wing and backwards have been analyzed. Sky Scout fixed-wing drone has been used to build the hybrid UAV, and the performance has been successfully demonstrated through flight tests. This paper precent the complete design of a quadrotor fixed-wing hybrid aerial vehicle with modelling, simulation and experimental verification.

Machine vision has been widely deployed in many industrial applications. However, the accuracy and maturity level for the inspection of through-hole technology (THT) solder joints have yet to reach its ultimate goal. In this paper, we have presented a detailed explanation on a set of novel algorithms that can be effectively used to implement an automatic vision system that is capable of classifying the quality of THT solder joints very precisely. This vision system can be easily integrated into a soldering robotic system that performs automatic soldering on THT solder joints. The proposed vision system is capable of controlling the entire robotic system while providing automatic rework capability on the defective solder joints with much less user interaction. The experimental results indicate that the proposed system has an improved recognition rate and good resilience to noise and uneven illumination distribution.

In recent years, Convolution Neural Network (CNN) gained great success in many applications, especially in computer vision. Now adapting CNN inference on edge devices has become an active research area in embedded vision and hot topic in Edge AI. The primary design hurdles for implementing CNN inference on embedded systems are limited computational resource, memory resource, and power budget. This study presents a novel architecture for SqueezeNet [1] like CNN models, which can be extended to support any CNN model as well. We address two approaches to mitigate resource constraints. First, we use a custom floating point(12 bit for computation and 8bit for storing). Second is slicing the model into a repetitive block called computation blocks. Computation block can be configured dynamically by the host processor to operate in a different mode. We have implemented SqueezeNet v1.1 for …

A low-complexity 4-D sparse FIR hyperfan filter is proposed for volumetric refocusing of light fields. By exploiting the partial separability of the spectral region of support of a light field, the proposed filter is designed as a cascade of two 4-D hyperfan filters. The sparsity of the filter coefficients is achieved by hard thresholding the nonsparse filter coefficients. The experimental results confirm that the proposed 4-D sparse FIR hyperfan filter provides 72% mean reduction of computational complexity compared to a 4-D nonsparse FIR hyperfan filter withoudeteriorating the fidelity of volumetric refocused light fields. In particular, the mean structure similarity (SSIM) index between the volumetric refocused light fields by the proposed sparse filter and the nonsparse filter is 0.989.

This paper presents the development of a Sinhala Speech Recognition System to be deployed in an Interactive Voice Response (IVR) system of a telecommunication service provider. The main objectives are to recognize Sinhala digits and names of Sinhala songs to be set up as ringback tones. Sinhala being a phonetic language, its features are studied to develop a list of 47 phonemes. A continuous speech recognition system is developed based on Hidden Markov Model (HMM). The acoustic model is trained using the voice through mobile phone. The outcome is a speaker independent speech recognition system which is capable of recognizing 10 digits and 50 Sinhala songs. A word error rate (WER) of 11.2% using a speech corpus of 0.862 hours and a sentence error rate (SER) of 5.7% using a speech corpus of 1.388 hours are achieved for digits and songs respectively.

The design and hardware implementation of a low-complexity signal processing algorithm is proposed for real-time depth-velocity filtering in 5-D light field videos (LFVs). The proposed design is based on a stable 5-D infinite impulse response digital filter having three cascaded sections, each synthesized using the concept of multidimensional passive network resonance. A novel semi-systolic hardware implementation is proposed. Each section of the filter is implemented and tested on a Xilinx Virtex-7 FPGA platform using MATLAB-based hardware co-simulation with both synthetic and real LFV signals. A real-time processing throughput of 467 LFV frames/s is implied with each section of the filter operating at 204, 164, and 115 MHz for input LFV frames of size 9 × 9 × 220 × 360.

Purpose Automatic Optical Inspection (AOI) systems that are extensively used in the industry of Electronics Manufacturing Services (EMS), performs the inspection of Surface Mount Devices (SMD). One of the main tasks of such an AOI system is to align a given PCB to the parameters of the corresponding PCB positioning system by a process called fiducial alignment. However, no detailed analysis has been carried out so far on the methodologies that can be used to have a very precise identification of PCB fiducial points. In our research, we have implemented an AOI system for the inspection of soldering defects of Through Hole Technology (THT) solder joints, which can be integrated to a desktop soldering robotic platform. Such platforms are used in environments where no specific lighting conditions can be provided within a surrounded atmosphere. Therefore, an AOI system that is capable of performing fiducial alignment of any given PCB under varying lighting condition is highly preferred. In this paper, we have presented a detailed analysis on feature extraction and template matching algorithms that can be used to implement a very precise fiducial verification process under normal lighting condition. Design/methodology/approach A detailed analysis and performance evaluation have been carried out in this paper on prominent image comparison algorithms that are extensively used in the field of image processing. Findings According to the analysis carried out in this paper, it could be observed that the combination of feature extraction and template matching algorithms gives the best performance in PCB fiducial verification process. Research …

Light field signal processing allows manipulation of a rich set of information captured from a scene to achieve real-time depth filtering and occlusion suppression. Low-complexity four-dimensional infinite impulse response digital filters for simultaneous depth filtering and occlusion suppression over multiple depths in light fields are proposed. A low-complexity two-dimensional separable approach is employed to design the proposed filters having multiple frequency-planar pass-bands/stopbands in the four-dimensional spatial frequency domain, that can be electronically tuned to enhance/reject planar objects at multiple depths in a light field. Filter synthesis details are provided with specific design examples corresponding to 2-passband and 1-stopband cases. Numerically generated and Lytro camera captured light fields are used to verify the effectiveness of the proposed multi-depth-pass and multi-depth-reject …

This paper presents an analytical framework to investigate the performance of full duplex (FD) device-to-device (D2D) networks where devices in a cluster are capable of caching popular content. Assuming spatially randomly distributed D2D users in the cluster where the users request for content according to the Zipf distribution, analytical expressions are derived for the device communication probability, coverage probability, cluster average spectral efficiency, and content average download latency of the system. The system performance metrics are derived for the three device operating modes of FD only mode, half duplex (HD) only mode, and mixed FD/HD mode. Numerical results show that the mixed FD/HD mode is the most appropriate communication mode for cache enabled FD D2D networks to achieve the highest cluster average spectral efficiency and low content average download latency.

A 3-D finite-extent impulse response (FIR) frustum filter having sparse coefficients is proposed for enhancing broadband plane waves (PWs) received by uniform aperture arrays. Motivated by the design technique of 1-D interpolated FIR filters, the proposed filter is realized by cascading a spatially-upsampled 3-D FIR prototype filter having a frustum-shaped passband and a 3-D FIR masking filter having a parallelepiped passband. Sparsity of the filter coefficients is achieved through the spatial upsampling of the coefficients of the prototype filter and by hard-thresholding the coefficients of both prototype and masking filters. The proposed 3-D FIR frustum filter saves 39.5% multiplications and 66.6% additions compared to the state-of-the-art 3-D FIR frustum filters without degrading the performance in enhancing broadband PWs.

This paper presents the implementation of a two-dimensional (2-D) finite-impulse-response (FIR) trapezoidal filter based beamforming array receiver. A 2.4 GHz 16-element receive-mode IQ array is designed and used for physically measuring the beam patterns corresponding to 2-D FIR trapezoidal filters. The 16-element beamformer is implemented using the reconfigurable open architecture computing hardware version-2 (ROACH-2) field programmable gate array (FPGA) platform to perform analog to digital conversion and digital signal processing. The 2-D FIR trapezoidal filter is designed as a 16-spatial input 32-tap filter and is implemented targeting the ROACH-2’s Xilinx Virtex 6 (sx475t) FPGA chip as a filter-and-sum architecture. The receiver array is precisely rotated (keeping the transmitter fixed) to digitally measure the received energy by integrating the instantaneous power of the output of the 2-D FIR …

Convolutional Neural Networks (CNNs) are widely used in deep learning applications, e.g. visual systems, robotics etc. However, existing software solutions are not efficient. Therefore, many hardware accelerators have been proposed optimizing performance, power and resource utilization of the implementation. Amongst existing solutions, Field Programmable Gate Array (FPGA) based architecture provides better cost-energy-performance trade-offs as well as scalability and minimizing development time. In this paper, we present a model-independent reconfigurable co-processing architecture to accelerate CNNs. Our architecture consists of parallel Multiply and Accumulate (MAC) units with caching techniques and interconnection networks to exploit maximum data parallelism. In contrast to existing solutions, we introduce limited precision 32 bit Q-format fixed point quantization for arithmetic representations and …

There are several systems that use one or several Kinect sensors for human gait analysis, particularly for diagnosis of patients. However, due to the limited depth sensing range of the Kinect—a sensor manufactured for video gaming—the depth measurement accuracy reduces with distance from the Kinect. In addition, self-occlusion of the subject limits the accuracy and utility of such systems. We overcome these limitations by using a two-Kinect gait analysis system and mechanically moving the Kinects in synchronization with the test subject and each other. This increases the practical measurement range of the Kinect-based system whilst maintaining the measurement accuracy. Results of the comparison of knee flexion, step length, and stride length with a software based method show that our moving Kinect system can accurately analyse these gait parameters.

This paper presents a novel low-complexity VLSI architecture for an EEG Feature Extraction Platform for wearable health monitoring systems. It integrates a processing core unit, preprocessing FIR filter block and an FFT accelerator. The platform supports 8 scalp EEG channels and it can be scaled up to 16 or 32 EEG channels. In this paper, we analyze several architectural optimizations for hardware implementation of features such as Power Spectral Density, Discrete Wavelet Transform, Autoregression etc. The proposed architecture is easily scalable to new feature extractors. An FFT accelerator is proposed to improve the flexibility of the platform. We provide a comparison with software models for each feature extractor and also validate the platform by implementing a seizure detection algorithm on CHB-MIT Scalp EEG database with an accuracy of over 95%.

This paper proposes and analyzes a distance-based duplex mode switching scheme for maximizing the average throughput of a cellular network and its underlay device-to-device (D2D) network. For each duplex mode of the cellular network, a node distance based duplex mode selection scheme is proposed to maximize the throughput of the D2D network. The proposed duplex mode selection scheme provides average throughput improvements in the range of 10%-200% for the D2D network compared to the always half-duplex and always full-duplex communications for high D2D user scatter variances.

Video synopsis, summarizing a video to generate a shorter video by exploiting the spatial and temporal redundancies, is important for surveillance and archiving. Existing trajectory-based video synopsis algorithms will not able to work in real time, because of the complexity due to the number of object tubes that need to be included in the complex energy minimization algorithm. We propose a real-time algorithm by using a method that incrementally stitches each frame of the synopsis by extracting object frames from the user specified number of tubes in the buffer in contrast to global energy-minimization based systems. This also gives flexibility to the user to set the threshold of maximum number of objects in the synopsis video according his or her tracking ability and creates collision-free summarized videos which are visually pleasing. Experiments with six common test videos, indoors and outdoors with many …

This paper proposes a novel channel estimation method and a cluster-based opportunistic scheduling policy, for a wireless energy transfer (WET) system consisting of multiple low-complex energy receivers (ERs) with limited processing capabilities. Firstly, in the training stage, the energy transmitter (ET) obtains a set of Received Signal Strength Indicator (RSSI) feedback values from all ERs, and these values are used to estimate the channels between the ET and all ERs. Next, based on the channel estimates, the ERs are grouped into clusters, and the cluster that has its members closest to its centroid in phase is selected for dedicated WET. The beamformer that maximizes the minimum harvested energy among all ERs in the selected cluster is found by solving a convex optimization problem. All ERs have the same chance of being selected regardless of their distances from the ET, and hence, this scheduling …

Biological sampling for biomass estimation is a highly labor intensive process that can benefit from automation using computer vision. In this paper two algorithms the Green Layer Extraction (GLE) method and Morphology and Marker Controlled Watershed Transformation (MMCWT) method are proposed for the estimation of frond (leaf) area of an invasive aquatic fern Salvinia molesta. The two algorithms are tested using a computer controlled automatic testbed. The mean accuracy for the GLE was found to be 89.66% for estimating the number of fronds and 86.74 % for estimating the frond area. For the MMCWT the respective results are 91.92% and 80.68%. Then the results are subsequently used for developing a mathematical model as growth rate estimation of Salvinia molesta for various concentrations of Sodium di-hydrogen phosphate.

Human gait analysis, the study of human locomotion, is possible with low-cost RGBD sensors such as the Kinect sensor. However, due to the inherent depth sensing accuracy limitations of these sensors as the distance from the sensor increases, the distance range of gait analysis too becomes small and inefficient for clinical use. We present a system that uses two independent Kinects in a data fusion framework that increases the distance range of gait analysis from 2.5 m to 4 m with three gait cycles. Our gait parameters are reasonably accurate and comparable with existing systems with 4% error in length measurements and 5° error in flexion measurements. The system is extensible to have several Kinects.

This paper presents learning and teaching experiences gathered from an induction program conducted at the Department of Electronic and Telecommunication Engineering, University of Moratuwa, Sri Lanka for newly enrolled undergraduate students. The induction program, named as the pre-academic term, was an experimental effort to explore the applicability of blended leaning concepts to enhance the learning experience of Engineering freshmen, while enabling smooth transition from high school to university education. In addition to standard lectures, an integral part of the program was in-class demonstrations, where electronic circuits were assembled from scratch on a printed circuit board and demonstrated using a projected camera during the lectures. Organization, learning objectives, brief description of the example projects are presented along with a summary of formal student feedback. More than 85 …

An analytical method to derive a DC-DC converter topology for an arbitrary voltage conversion ratio is presented in this paper. The proposed method can be employed to derive DC-DC converters based on single and multiple inductors. The derivation of DC-DC converters having single inductor is explained in detail with a brief introduction to the multiple inductor derivation. The basic switching cells that can be incorporated into the single inductor based converters to obtain higher gain is introduced. Furthermore, their use to realize existing converter topologies is illustrated to validate the applicability of the proposed method to derive converters having an arbitrary gain.

This paper proposes a high step-up boost converter family which is based on a switched coupled inductor (SCL) and a voltage litter cell. The derivation of converter topologies of the family using SCL and voltage litter cell is explained in detail. The operation of the converters is explained using the converter which has the highest gain. The operation of the other converter topologies can be explained using a similar approach. The converter with the highest gain is theoretically analyzed assuming its operation in the continuous conduction mode (CCM) to obtain expressions for the static voltage gain, capacitor voltages, voltage stresses of switching elements, inductor currents and boundary mode operation. The operation of the converter is validated using simulation assuming near ideal conditions.

A family of ultra-high step-up DC-DC converters based on a feed-forward capacitor and a coupled-inductor is proposed. The voltage conversion ratio of the proposed converter family is a polynomial of the turns ratio of the coupled-inductor which is obtained by the time-multiplexing operation of the coupled-inductor and the feed-forward capacitor. The time multiplexed operation of the coupled inductor is explained with ideal waveforms which are employed to derive a generalized expression for the voltage conversion ratio of the proposed converter family. The operation of the proposed converter family is verified using simulation results.

In this paper, a feasibility study for construction and control of a novel design of a Multi-quadrotor unmanned aerial vehicle (UAV) is presented. This novel concept tests four identical Quadrotors assembled in a bigger cross structure. And, it also tests the ability of using the same controller that is used to control a single quadrotor to fly the novel design of cross assembled four quadrotor UAV. The main objective here is to improve redundancy and robustness and load carrying capacity of quadrotor UAVs. Even though there are four quadrotors, there is only one controller involves. When each individual Quadrotor works on a certain flight maneuver, it is expected that the assembled UAV of four of these in a cross structure to also be able to demonstrate the same maneuver. The prototype of the novel UAV was designed and built, and has been experimentally tested for a proof of concept where it was able to stabilize the …

Due to high costs at initiation, alternative communication strategies to dedicated short range communication (DSRC) have been looked at to facilitate quick deployment of intelligent transportation services. Wi-Fi Direct (WD), has come across as a candidate, and this paper focuses on the drawback of large transmission delays in WD. To this end, it studies the performance gains of using a broadcast mechanism on the downlink between the group owner (GO) and the clients of a WD group, instead of the currently used peer-to-peer method. Gains in terms of average total delay and the average energy consumption of the GO are presented using a theoretical analysis as well as a simulation study using OMNeT++. It is also shown that the degradation in performance on the downlink due to not having retransmissions is within tolerable limits given that the size of the group is selected properly.