Robotics and Computer Engineering - Master's theses

Selle kollektsiooni püsiv URIhttps://hdl.handle.net/10062/42116

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A symmetrical DC-to-DC converter for capacitive energy swinging
(Tartu Ülikool, 2020) Syzoniuk, Oleksandr; Must, Indrek; Banerji, Saoni; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Soft Robotics is a specific robotics subfield that is involved in building robots from highly compliant materials like those found in living organisms. The energy management system is a fundamental aspect of evaluating the energy-autonomy of soft robots. To date, energy management systems for soft robots with ionic capacitive laminate (ICL) actuators are ineffective and cannot re-use energy, which is irrevocably lost after, each cycle of the robot actuation. Thus, there is a need to provide a suitable energy-conditioning circuit that would allow the re-use of energy between several ICLs at once. In this thesis, we propose a door to energy management solution through design: asymmetrical bidirectional DC-to-DC converter that could transfer energy between ICLs for prolonged power-autonomous operation. The proposed solution has the scope to revise the current soft robots in terms of energy management. The idea of increasing energy transfer efficiency will result in efficient soft robots in rescue missions (for instance), that will have a significant impact in the world.
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An Open-Source Robotic Study Companion for University Students
(Tartu Ülikool, 2023) Baksh, Farnaz; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
This thesis presents an evidence-based approach and develops an affordable and effective Robotic Study Companion (RSC) prototype for university students. It addresses the lack of social robots tailored to higher education and the scarcity of open-source educational platforms. Through a comprehensive literature review on Human-Robot Interaction (HRI), social and companion robots, and Natural Language Processing (NLP) technologies, this work identifies trends and best practices for educational social robots. The research systematically reviews select social robots, examining their applications, technical features, design, and human-centric interaction. It explores the human perspective of HRI, focusing on users in educational settings. Based on these insights, functional and non-functional requirements are established for the RSC, inspiring its design and development. The RSC prototype, built using off-the-shef components and leveraging OpenAI's large language models, demonstrates its potential to simplify complex concepts for students. The long-term goal is to enhance the RSC's design, durability, and commercial viability.
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Analysis of variations in orbital parameters of CubeSats
(Tartu Ülikool, 2014) Ploom, Indrek; Tartu Ülikool. Loodus- ja tehnoloogiateaduskond; Tartu Ülikool. Tehnoloogiainstituut
Käesolev töö uurib variatsioone kuupsatelliitide orbitaalparameetrites, et selgitada kuidas orbitaalparameetrid ajas muutuvad, millised omavahelised seosed on parameetrite vahel, kuidas nad mõjutavad satelliidi eluiga ning kuidas erinevad häirivad jõud mõjutavad orbiite. Töö tulemused on suunatud rahvusvahelisele/ülemaailmsele nanosatelliitide arendajate huvigruppidele. Kuupsatelliidi standard on osutunud populaarseks ja huvi järjest kasvab. Missiooni planeerimise ja satelliidi disaini seisukohast on väga oluline teada seda, kuidas satelliidi eluiga on seotud tema massi, suuruse, kuju, orbitaalparameetritega ning kuivõrd suure mõjuga erinevad häirivad jõud orbiidis hälbeid tekitavad. Kuupsatelliitide orbitaalparameetrite käitumist ei ole varem uuritud, küll aga on varasemalt uuritud üksikuid suuremaid satelliite väga täpselt mõõdetud parameetritega. Käesolev töö ei tee ise mõõtmisi vaid kasutab massiliselt ära vähem täpsemaid ja vabalt kättesaadavaid ajaloolisi orbiidi andmeid Two-Line Element (TLE) formaadis, mis oma esialgses lähenduses on mõeldud raadioamatööridele ja hobi-astronoomidele. TLE-s sisalduvate värskete hetke- orbiidiandmete ja erinevates tarkvarades rakendatud liikumismudelitega on võimalik ennustada objekti liikumist ning suunata oma antennid suhtluseks õigeaegselt vajalikus suunas. Töö uurib ka TLE-de sobivust orbitaalkäitumise analüüsiks ja tulemuste kasutatavust tegeliku missiooni planeerimise ja disaini juures. Töö käik on olnud väga huvitav ja kestnud umbes aasta, See on hõlmanud muuhulgas andmete kogumist, töötlust, kvaliteedi hindamist. Tööd (MySQL) andmebaasiga – andmete jaoks sobiliku struktuuri loomist, andmetega täitmist ja sobival kujul andmete esitamist. Andmeanalüüsi, mille osana kasutati ka GNUPlot nimelist tarkvara orbitaalparameetritele graafilise vormi andmiseks.
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Assessing Event-Based Localization Algorithms for Vehicular Off-Road Applications
(Tartu Ülikool, 2023) Salumets, Sten; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Event cameras, with their high temporal resolution and dynamic range, represent a promising technology for localization applications. Yet, their performance in off-road environments remains untested. This thesis addresses this gap by assessing three eventbased localization methods in off-road settings. A conventional frame-based method is included as a benchmark for comparison. The effectiveness of each method is assessed by comparing computed trajectories with ground truth data. The findings indicate that current publicly available event-based methods are not yet mature enough to provide accurate and robust performance in off-road environments. The study underscores the need for further research to fully harness the potential of event cameras in these challenging settings.
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Assessment of ethnic and gender bias in automated first impression analysis
(Tartu Ülikool, 2022) Krull, Friedrich; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
This thesis aims to investigate possible gender and ethnic biases in state-of-the-art deep learning methods in first impression analysis. Analysing a person with some software, businesses want to find the best candidate, without the person being judged by their gender or ethnicity. To achieve this, a first impression dataset about the big five personality traits, with additional information about the person’s gender and ethnic background, was used. Biases were both investigated with models trained on balanced and imbalanced data, where balanced here refers to the number of frames used from people classified as Asian, African-American, or Caucasian in the dataset. The results with both the balanced and imbalanced datasets were similar. With all the models the accuracy for Asians was much higher compared to others, which may come from the fact that the dataset did not include enough variance in the Asian data, so when evaluating, all Asians were seen similarly.
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Asymmetric Deep Multi-Task Learning
(Tartu Ülikool, 2024) Maharramov, Ali; Matiisen, Tambet; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Recent developments make deep neural networks a valuable asset for autonomous driving. They can be deployed as an end-to-end system or part of more complex systems for specific tasks. If a system needs several tasks by neural networks, using multi-task learning (MTL) introduces few benefits compared to deploying several single-task learning (STL) models, such as better time and space complexity on deployment and potentially increased generalization on the backbone network. However, MTL often faces unique challenges. Many existing MTL datasets have limited labels or lack the required labels for specific tasks, and generating labels for these tasks leads to resource and time consumption for researchers. Training the model on an asymmetric labeled dataset, a dataset where labels for specific tasks are unavailable for a subset, can cause a biased gradient, reflecting an unbalance in the accuracy of tasks. In this thesis, asymmetric MTL were investigated and compared to symmetric MTL and STL methods.
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Augmented reality (AR) for enabling human-robot collaboration with ROS robots
(Tartu Ülikool, 2022) Rybalskii, Igor; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
With current industrialization trends on the reintroduction of human into the manufacturing process and development of augmented reality I propose the interface, which uses Augmented reality to allow the operator to interact with robotic systems, such as manipulators and mobile robots. 2 interfaces were created: one for manipulators and one for mobile robots. Both of them are developed to work on Microsoft Hololens 2 augmented reality glasses and robots, running ROS. Interface for manipulators allows user to control the robot by sending end-effector goals and previewing the goal joint states of the manipulator. Interface for mobile robots allows the user to send navigation goals and preview the robot’s movement trajectory. Interfaces were developed using Unity game engine. Developed interfaces were tested with UR5e manipulator and Robotont mobile robot.
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Automating data management system of 1.5-meter telescope at Tartu Observatory
(Tartu Ülikool, 2020) Suchockas, Laimonas; Eenmäe, Tõnis; Ramler, Heleri; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
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Autonomous motion planning for spacecrafts near small solar system bodies: simultaneously refining the gravitational field model and re-planning gravity dependant maneuvers
(Tartu Ülikool, 2020) Paul, Aditya Savio; Otte, MichaelW.; Allik, Viljo; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Small solar system bodies can be better studied while orbiting in their vicinity. However, orbital motion around such bodies is challenging due to their irregular and weaker gravity as compared to larger bodies. Moreover, a-priori paths developed by earth-based measurements tend to generate monolithic trajectories. Dynamic path planning in space has the potential to improve the study of small solar system bodies. Fine-grained motion plans require detailed knowledge of the gravitational forces, that can be measured in the sphere of influence. The gravity models can be analysed for mass and material distribution across the body. We propose a method for autonomous motion planning around small solar system bodies that simultaneously measures and refines the gravitational model. The trajectories are replanned considering the updated model to perform stable orbital maneuvers eventually providing a high fidelity gravity model. The research shall enable the spacecraft to perform autonomous maneuvers, design landing strategies and scout for in-situ resources.
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Avatud robotplatvorm Robotont
(Tartu Ülikool, 2019) Raudmäe, Renno; Kruusamäe, Karl, supervisor; Vunder, Veiko, supervisor; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Robootika osakaal maailmas on tõusmas ning suur osa sellest tuleneb teenindusrobootikas kasutatavatest mobiilsetest platvormidest, mis tingib erakordselt suure nõudluse robootika inseneride järele. Käesoleva magistritöö eesmärgiks oli ROSi toetava haridusliku robotplatvormi Robotont arendamine. Lõputöö raames seati töökorda kuus Robotont generatsioon 1 ning valmisid õppematerjalid antud platvormile. Loodi Robotont generatsioon 2 mehaanika disain, lahendus, dokumenteerimise keskkond ning toodeti 17 Robotont generatsioon kahte. Valminud robotite töökindlust testiti mitmetes töötubades ja Tartu Ülikooli Narva Kolledžis kursusel „Robotite programmeerimine ROS vahenditega“.
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Broadcast Systems: Alamouti Index Coding
(Tartu Ülikool, 2017) Atanda, Abdulazeez Olaseni; Skachek, Vitaly, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Consider a wireless broadcast channel with a number of receivers, where each receiver possesses some side information. In an index coding problem, the transmitter aims at delivering different messages to different receivers. It is desirable to minimize the total number of message transmissions in order to improve the bandwidth efficiency. It is known that the minimum number of transmissions can be achieved by solving a minimum rank problem for a given side information graph, which is a known NP-hard problem. In this thesis, the index coding problem over additive white Gaussian noise and Rayleigh fading channels is studied. Modulation techniques, such as phase shift keying and quadrature amplitude modulation, are tested, and it is shown that a careful choice of modulation can improve the performance. It is also shown that a careful choice of a generator matrix can provide for further performance gains, in particular for ”prioritized” receivers. A probabilistic soft information detection (PSID) is compared to a simple hard decision scheme, and the PSID performance is shown superior in achieving a lower error rate. Additional improvement in performance is achieved by using diversity, when employing two transmit and two receive antenna system in conjunction with the Alamouti code. All these techniques provide for the lower error rates and higher throughput when compared to the traditional schemes.
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Building an Efficient and Secure Software Supply Pipeline for Aerial Robotics Application
(Tartu Ülikool, 2019) Arsovska, Dzvezdana; Kruusamäe, Karl, supersivor; Sheremet, Illia, supervisor; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Unmanned aerial vehicles (UAVs) used for wind turbine inspection need robust software testing and deployment strategies which go beyond the traditional pre-deployment validation on real hardware. The goal of this thesis is to implement secure software supply pipeline within a case organization and evaluate the results of the implementation. The pipeline leverages the Docker containerization environment coupled with the advancements in Continuous integration and Continuous delivery practices. The result of this thesis is an automated testing and delivery pipeline which can be used for testing single components as well as the system as a whole in an efficient way, effectively reducing the time and effort required to make a new release.
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Capturing the sound of reed instruments via measurement of reed strain
(Tartu Ülikool, 2023) Pihlap, Meelis; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
The sound from reed instruments (such as the bagpipe or the clarinet) is conventionally captured using microphones. Microphones capture all sound regardless of source, making it a volatile choice in live settings, where background noise (e.g. from other instruments) is prominent. As such, an instrument pickup for reed instruments is desirable for use in settings where an isolated signal is required. There are few existing reed instrument pickups and their installation often involves permanent changes to the instrument. A novel reed instrument pickup is introduced, which uses a strain gauge mounted directly to the oscillating tongue as the sensing element. The pickup is compared against a measurement microphone and the results show that after a filtering stage, the pickup sounds good enough to compete with the microphone.
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Communications subsystem hardware and software development for the ESTCube-2 nanosatellite
(Tartu Ülikool, 2021) Allaje, Kristo; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
One of the most crucial components of satellites is their communications subsystem. Without a functioning radio link, it would be challenging to receive telemetry and payload data from the satellite and send telecommands to it from the ground. ESTCube-2 is a 3U CubeSat from the Estonian Student Satellite Foundation that is expectedto launch in 2022. The mission of ESTCube-2 is to test various payloads inLEO. The primary payload being the plasma brake, similar to the Electric Solar Wind Sail (E-Sail) experiment on ESTCube-1. Due to the critical nature of the satellite communications system, it is essential to start with thorough testing early to reach high reliability by the launch. The goals for this master thesis are to test ESTCube-2 communications subsystem hardware and software, and to create an engineering model, to resolve any issues discovered.
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Comparison of Water Detection Models for an Off-road Unmanned Ground Vehicle
(Tartu Ülikool, 2023) Rustambayli, Fidan; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Water hazards can cause unmanned ground vehicles (UGVs) to become stuck or break down during an autonomous mission, damage electronic components and sensors, and require costly repairs or replacements, making it crucial for UGVs to identify water hazards in real-time, determine secure path around them, or reduce their speed when appropriate to cross them safely. This thesis proposes a water detection system for UGVs in off-road environment. The proposed approach combines convolutional neural networks (CNNs) with transfer learning, leveraging their capabilities for effective water detection. The thesis includes a comprehensive review of traditional sensor-based methods and recent deep learning-based techniques. Real-world data collected in off-road environments are utilized to evaluate the proposed approach, and the method achieves a 0.50 Mean-IoU score and 92.74% accuracy on the test dataset. We also include a comparative analysis of the method with a previous deep learning-based semantic segmentation method for water detection. The comparison provides insights into the relative strengths and weaknesses of these approaches for water detection in off-road environments. Overall, this thesis provides valuable insights into the use of deep learning for semantic segmentation in challenging environments.
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Comprehensive Study on High Dynamic Range Tone Mapping with Subjective Tests
(Tartu Ülikool, 2017) Salahlı, Aygül; Anbarjafari, Gholamreza, juhendaja; Ozcinar, Cagri, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
A high dynamic range (HDR) image has a very wide range of luminance levels that traditional low dynamic range (LDR) displays cannot visualize. For this reason, HDR images are usually transformed to 8-bit representations, so that the alpha channel for each pixel is used as an exponent value, sometimes referred to as exponential notation [43]. Tone mapping operators (TMOs) are used to transform high dynamic range to low dynamic range domain by compressing pixels so that traditional LDR display can visualize them. The purpose of this thesis is to identify and analyse differences and similarities between the wide range of tone mapping operators that are available in the literature. Each TMO has been analyzed using subjective studies considering different conditions, which include environment, luminance, and colour. Also, several inverse tone mapping operators, HDR mappings with exposure fusion, histogram adjustment, and retinex have been analysed in this study. 19 different TMOs have been examined using a variety of HDR images. Mean opinion score (MOS) is calculated on those selected TMOs by asking the opinion of 25 independent people considering candidates’ age, vision, and colour blindness.
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Concept of a Robotic Beehive Based on a Case Study with a Beekeeping Company
(Tartu Ülikool, 2025) Väljaots, Mihkel; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Throughout history, beekeepers have developed new types of beehives to improve beekeeping efficiency and enhance honeybees' quality of life. In the past five years, the trend in innovation has shifted toward full automation, with many examples emerging. This thesis follows that direction by investigating one professional beekeeping company, using a case study as the primary research methodology. This thesis explores the research questions: 'Which parameters are inspected by beekeepers?' and 'How can the beehive be automated based on these parameters?'. Participant observation, the researcher's diary, a semi-structured interview and digital imaging were used as data collection methods to gather and validate information relevant to the automation of the beehive. A custom imaging device was developed and employed to acquire approximately 3000 frame images across more than 100 Langstroth beehives. These images served as input for evaluating Varroa destructor detection performance using the YOLO-based computer vision system. It was observed that the case study partner (whose core business is honey production) does not measure any specific parameters in the beehive to run a successful beekeeping business. Decisions and actions are based on the evaluation of 20 parameters, the most important of which are the queen's health, temperature, and available space for brood and honey. The greatest challenge in automating the beehive is the localisation of the queen. A magnetic tag and smart frames with digital magnetic sensors are proposed to address this issue. The second challenge involves moving frames that are stuck together, as breaking them loose can sometimes require more than 300 N of force. The third challenge is to move frames between beehive bodies while keeping honeybee losses as low as possible. The collected information was analysed, and the requirements for a robotic beehive are presented along with the overall concept of the robotic beehive. The case study partner describes the perfect beekeeper as someone who 'sees everything and remembers everything.' Since the partner relies on very general notes when making decisions in beehive management, and it is not feasible for humans to memorise images of thousands of frames, a robotic beehive equipped with computer vision and hive management functions is relevant from both scientific and commercial perspectives. It is recommended that the first development phase of robotic beehives be developed to explore possible visual patterns and sound or temperature signatures that could transform beekeeping operations in unprecedented ways.
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Continuous Collaborative Mapping in Unknown Environments: A Multi-Robot System Approach
(Tartu Ülikool, 2024) Radigon, Malcom; Muhammad, Naveed; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Navigating and exploring unknown terrains remains a critical challenge within the field of mobile robotics. Achieving rapid and consistent exploration is crucial for the prompt generation of precise maps. This thesis introduces a cutting-edge distributed exploration system utilizing a multi-robot fleet. This innovative system is crafted to facilitate continuous exploration in unexplored areas by implementing a novel dronebased communication relay method. Additionally, it enables the synthesis of an integrated, comprehensive global map, providing crucial, rapid insights for human operators into the explored areas. The effectiveness of this system has been thoroughly evaluated through a series of simulated experiments encompassing various trials. These evaluations underscore the system’s capability in smoothly conducting exploration tasks, notably overcoming delays traditionally linked to communication challenges.
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Deep Learning Based Automated Job Candidate Interview Screening
(Tartu Ülikool, 2019) Aktas, Kadir; Anbarjafari, Gholamreza, supervisor; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
Traditional way of recruitment process is challenging for both the candidate and the employer. To apply for a job, the candidate needs to prepare a CV. On the other hand, the employer needs to check all the submitted CVs and analyze the candidate data manually. These aspects can make the process very time consuming, especially when there are many candidates. Furthermore, the manual analysis of the candidate data is very open to human bias. The thesis proposes an automated video interview analysis system, which eliminates the problems mentioned above.
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Design and Characterization of an Ultra-Wideband Radio for Extended-Range Transmission
(Tartu Ülikool, 2025) Vaht, Oliver; Kalde, Jaanus, juhendaja; Tartu Ülikool. Loodus- ja täppisteaduste valdkond; Tartu Ülikool. Tehnoloogiainstituut
This thesis presents the design and characterization of a custom ultra-wideband radio system for extended-range communication. Existing commercial modules were found inadequate due to limited configurability and restricted frequency range. To overcome these issues, a UWB platform was developed, including a transceiver based on the DW1000 chip, a power amplifier using the Renesas F1485, and a pentagon-shaped antenna optimized for 3–5 GHz. All components were validated through measurements. Field tests were conducted in real outdoor conditions with a special frequency license. Maximum communication distance achieved was 2.63 km using UWB Channel 4. Bit error rate remained low, with packet loss becoming the main limiting factor at longer ranges. The results show that with custom hardware and correct configuration, UWB can be used effectively for extended-range transmission in real-world conditions.

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