The primary objective of the subsystem discussed in this report is to continuously estimate the transfer-response of the system using the position measured by the interferometer, in order to accomplish adapted model inverted control using a dynamically updating model. In addition, this subsystem design incorporates a controller that is crucial for obtaining undisturbed position measurements. This is achieved through a feedback loop that is controlling the DC operating point of the interferometer such that it is at its quadrature point.

Ultrasonic transducers are commonly used in a variety of medical, industrial, and consumer devices, con- verting electrical energy into high-frequency sound waves. These devices find extensive applications in fields such as medical imaging, non-destructive testing, distance measurement, and cleaning processes. However, these transducers suffer from a narrow operating frequency range caused by a steep frequency response curve with a prominent resonance peak. Existing passive compensation methods using filters are limited due to the individual characteristics of transducers and their susceptibility to process varia- tions, making generic compensation filters impractical. Additionally, the frequency response of transducers changes over time, input power, and environmental conditions, further complicating compensation efforts.

The objective of this project is to overcome these challenges by creating an integrated solution that can provide an ultrasonic transducer system with a consistent frequency response despite external disturbances. The proposed system will incorporate non-linear dynamics characterization and compensation, which are currently lacking in integrated solutions. By accurately characterizing the transducer’s non-linear behavior and compensating for it, the system will overcome the drawbacks associated with passive compensation.

The proposed integrated system holds promising implications for various applications, including med- ical imaging, material testing, and industrial processes. By mitigating the limitations associated with the narrow operating frequency range of ceramic piezoelectric transducers, this research project contributes to the advancement of ultrasonic technology and its broader impact on diverse industries.

The idea of autonomous driving was merely just a dream about 5 years ago but now, with the advancements in technology, it has become prevalent. The aim of this thesis is to provide a low-cost approach for detecting and tracking moving objects from a moving platform. This could be used for an autonomous vehicle to automatically avoid moving objects. Our low cost approach will use a raspberry-pi processor board as computation platform and stereo cameras as sensors. The process of multiple moving objects detection is performed by initially calculating the disparity maps from the stereo image pairs. Following this is the generation of point cloud data from the disparity map which is followed by semantic segmentation and generation of object proposals. An EKF based tracker is used to track the moving objects across the frames.

Designing the future of work is a goal that is currently being tackled by both industry and academia. In a scenario where we have Human-Robot hybrid teams, it will be necessary for both human and robots to be aware of each other in their respective tasks. This thesis explores how specific robots (cobots - collaborative robots) can use Computer Vision-based methods for awareness of a human's presence, while using this data to influence the cobot's own behaviour.
After explorations of the Computer Vision field in regards to this problem, and selected approaches in the domain of Human Awareness for Human-Robot Interaction in literature, this thesis presents a proof of concept software/hardware system that, given all the apriori findings, implements simple demos that demonstrate both the feasibility and the suitability of a pure vision-based system for the problem of human awareness. It then analyses the strengths and weaknesses of the proposed system solution, ending with a road-map of recommendations for a following production prototype.

Distributed cooperative robots can be highly beneficial in mapping disaster environments and assisting with search and rescue operations. In most situations such environments only allow for only limited communication between robots. This thesis reports on simulation experiments conducted to test the impact of having only partial communication capabilities between cooperative agents on area exploration strategies. The Monte Carlo Tree Search (MCTS) planning algorithm has been utilised by multi-robot teams to cooperate and explore an environment effectively. On top of this base case, other communication scenarios are applied: No communication at all, and near-neighbor communication at various ranges. In addition to these communication strategies, robots are also given the ability to predict the paths of peers. From extensive simulation tests, it is shown that partial communication can recover a significant amount of performance in a limited communication environment. Giving agents a peer prediction ability is shown to have a positive effect in very specific situations. It is also shown that providing prior information of the environment obstacle locations to agents is not useful. Instead, increasing the number of chances of agents sharing information, positively effects the exploration performance.

With the requirements for CubeSats increasing, a push towards utilizing high­performance equipment has never been greater. Incorporating these equipment in an environment that is cost­, space­ and power­constrained, is challenging. Simultaneously, high­performance equipment require high pointing­accuracy and low­jitter. This thesis proposes the use of a cost­effective reaction­wheel, which utilizes three hall­sensors for accurate attitude­control. Additionally, the requirements state that the reaction­wheel operates in the low­speed region, whilst tracking low­acceleration commands. For this, a controller­structure is designed, simulated & implemented in order to provide accurate angular­velocity estimates at a constant rate. Whilst the angular­velocity estimates are within 1% of the measurements, the angular­acceleration tracking performance relies greatly on the noise of the reaction­wheel torque­friction. Nonetheless, the angular­acceleration mean error was found to be 0.005 RPM/s, with a variance of 0.3 RPM/s on a 0.01 RPM/s reference

The urgency for high-security products for industrial networks is increasing as malicious hackers are improving their accessibility tools. A common practice for a company to protect its sensitive data is network segmentation. The network is segmented in different domains with distinctive security levels. The sensitive data is stored and managed within the domain of the highest security level. To access this domain from another domain of a lower security level, a highly reliable connection is required. You want to have full control over the incoming and outgoing data flow between these network segments. A variety of solutions provide a highly-secured connection to link those segments which differ in range of features and control. An upcoming trend is the network diode. This device will allow data flow in only one direction. All the flows going into the opposite direction are being blocked. However, to feature an arbitrary flow between two network segments, the diode should consist of a numerous amount of properties. To narrow down the optional features a network diode should provide, this thesis will focus on TCP streams. TCP is one of the most common protocols used in internet traffic. Furthermore, TCP is a challenging protocol as it is a connection-oriented bidirectional protocol, which is intrinsic controversial with the concept of the data diode. To ensure the security of the data diode, this thesis will focus on a complete hardware design of the data diode. Software inside the data diode is still a risk for a security breach. This thesis will investigate the critical operations of TCP to implement them in the data diode. The aim is to utilise TCP's characteristic operations of the acknowledgement managing, the sliding window system, the congestion control algorithm, and explores the advantage of existing TCP options. To evaluate the feasibility of a high performance data diode featuring TCP, the system is broken down to project the behaviour of a TCP stream on a one-way connection device. This results in two separate TCP connections, with only the precious data as common shared information. This model requires a buffer at one side of the diode to transmit data in a TCP stream. To analyse and examine the influence of the diode configuration to the size of the buffer, a diode module is created to simulate in a OMNeT++ environment. From this simulation tool, a minimal set of parameters can be extracted that are essential to configure the data diode. With the assumption of having control on the network management at the trusted side of the diode, a configuration without a congestion control algorithm and without adding radical TCP options is recommended to minimise the required buffer size. Thereafter, this thesis proposes a high-level hardware design to implement the data diode on a hardware project. The design focuses on the high data rate which should be available to satisfy the data diode's requirements. Finally, this thesis concludes with an elaboration on the assumptions of the limitations of the network environments and recommends features to implement in future work.

The accelerating growth of the Internet of Things (IoT) has led to the development of many technologies for homes like a wireless lighting system. Unlike traditional lighting systems, these can be operated remotely using mobile devices and even with the help of a smart assistant, such as Amazon Alexa or Google Assistant. Zigbee is used as the standard of communication between the wireless lighting system whereas other Wi-Fi applications are also extensively used in homes. A common problem for wireless radios such as Wi-Fi and Zigbee is that they have to share the ISM band which could lead to coexistence issues. Zigbee has lower power and longer channel sense times than Wi-Fi which makes it more vulnerable to interference. Bandwidth hungry Wi-Fi applications such as multimedia streaming cause adverse effects on Zigbee’s performance and the system can become temporarily out of reach as the nodes cannot gain access to the channel. This results in inconvenience to the user as the system might not respond in such situations. As these standards are fundamentally different and it is almost impossible to operate on a non-overlapping channel especially with the wide deployment of Wi-Fi networks, a new centralized approach is proposed in this work to coordi- nate between the two heterogeneous networks. The Wi-Fi router which serves as a gateway for both networks in a home is utilized as a coordinator for these networks. By performing various experiments, we examine the lowest data rate for Wi-Fi at which Zigbee can transmit its packet in a reliable manner. We propose a system design that effectively converts a high Wi-Fi interference environment to a transient low interference environment during Zigbee transmission. By combining the packet detection capabilities of the Linux router firewall and a custom queueing setup, we show we can provide reliability to the wireless lighting system with zero to a minimum loss for Wi-Fi transmission. We detect the Zigbee packet well in advance which enables us to adopt a preventive approach rather than a reactive one. Our system design results in a decrease of Zigbee packet loss from 67% to 7% while maintaining an average RTT of 35 ms at every load. We keep the complexity of the system design low by only making software changes to the router and not introducing a new node for synchronization between the two networks. The performance analysis of the system design is done using a test bed consisting of multiple Zigbee and Wi-Fi nodes, with the Wi-Fi router acting as a central controller for both of these networks.

In the recent years the satellite industry has progressed on the subject of optical communication for use in space. With recorded speeds over 5 Gb/s it has shown to be an alternative for radio communication. In the CubeSat market this technology is new, underdeveloped, and could lead to new missions that were not possible before. As such, TNO and Hyperion joined forces to create the CubeCAT LCT (Laser Communication Terminal). The core part of this LCT is the high-speed digital data path, which was not implemented. This thesis discusses the design, implementation, and verification of the high-speed data path of the CubeCAT LCT (Laser Communication Terminal) that has a targeted speed of 100 Mb/s, with a future upgrade path to 1 Gb/s. The CubeCAT module consists of multiple modules, of which the DMU (Data Management Unit) hosts the high-speed data path. As the DMU was not implemented, a design for the DMU is proposed in this thesis. For this design multiple architectures, interconnects, and components where considered. The proposed design is based on an Hyperion CP400.85 microprocessor connected to a Lattice ECP5-5G FPGA, together with extra external memory and external storage. Then, an implementation of the high-speed data path was made that is based on a QSPI link between the microprocessor and the FPGA. This implementation is based on streaming the data from the microprocessor to the FPGA, in which the data is encoded according to the TNO3k FEC (Forward Error Correction) scheme. After encoding, the data is outputted as an LVDS signal to the laser output. The implementation of the high-speed data path was verified by simulation and on a development setup. This was done by first verifying all submodules, with focus on the QSPI link and the TNO3k encoder, and then as a whole system. All submodule tests were successful, with a note to the verification of the QSPI link. It was found that the development setup was limited to a SPI frequency of 41.50 MHz due to signal integrity issues. During the system test it was found that the there was a lack of LVDS test material. As such the LVDS output was replaced by a UART output. With this output the whole system has been validated for a QSPI link speed of 119.2 Mb/s and an internal FPGA speed of 3.2 Gb/s. The system, with LVDS output, is estimated to consume 1 watts of power. With the validation of the whole system, the high-speed data path of the CubeCAT LCT has been implemented. The design of the DMU allows for a later, 1 Gb/s upgrade of the high-speed data path.

In the field of automotive technology, the last decade has seen a rise in projects focusing on self driving vehicles. With this renewed interest from the industry and academic world, new solutions to improve the reliability and safety of these vehicles are required. In this thesis, a new method for information sharing between different vehicles is discussed. This method makes use of radar devices, already in use in the automotive sector for obstacles detection. More specifically, a communication channel will be created between two frequency modulated continuous wave (FMCW) radar devices, using the same waveform utilized for radar sensing. This work will focus on the obstacles to overcome in order to achieve correct data transmission between two radar devices. Different solutions will be evaluated, and a working system, achieving data transmission, will be implemented using radar evaluation boards provided by NXP semiconductors.

Elliptic Curve Cryptography (ECC) performance is a major performance bottleneck when serving many VPN clients from a single server on a low-frequency FPGA softcore CPU. Using an area-efficient Elliptic Curve Point (ECP) multiplication accelerator core on the same FGPA, a much higher amount of clients can be served using the same FPGA chip. Using the accelerator core, the obtained speedup ranges from 1.6x in a suboptimal configuration up to 7x with a configuration that maximizes the use of ECC when connecting new clients to the server. In this optimal configuration, the total amount of clients that can be served by a single OpenVPN server increases from 80 in the base case, to 350 in the accelerated case.

The company Kien 1 is developing Bluetooth Low Energy (BLE) speakers, consisting of a subwoofer and several satellite speakers. These subwoofer and satellite speakers will have a feature named Follow Me, which when enabled from a smartphone application, will play music only in the room where the user currently is. The BLE’s signals will encounter obstruction, reflection, and diffraction from obstacles such as people, walls, and furniture. These indoor propagation issues cause the received signal strength (RSS) to have more distortion and variate more. Indoor position systems (IPS) that make use of a geometric model, such as using the RSS in trilateration methods, will suffer greatly from the propagation issues. On the contrary, fingerprinting methods that use a statistical model are more robust. However, fingerprinting requires a time consuming setup that needs to be redone periodically and every time after the environment changes. We implemented a Naive Bayes Gaussian classifier that can distinguish whether the signals travelling between a pair of BLE speakers, which are placed in two fully furnished adjacent rooms, came from speakers in the same room or in different rooms. Subsequently, the speakers that are in the same room can be grouped together, which is a subtask for the Follow Me feature. The classifier uses two features derived from the RSS information. Namely, the mean of the sum of several RSS samples (MSUM) and the standard deviation of the RSS range of several sample sets (SRR). We have quantified the classifier’s robustness by evaluating its performance in 9 different environments that had obstacles or radio frequency (RF) interference or both. We chose the acceptable performance to be an area under the curve (AUC) of at least 80.00 %. The classifier was able to successfully distinguish between BLE speakers that were in the same room and in different rooms in 7 environments with a minimum and maximum AUC of 86.64 % and 100.00 %, respectively.

The mission control of a fixed-wings UAV is slightly more complex compared to other models like quad-rotors or unicycles since the dynamic of a fixed-wing aircraft does not allow rapid direction changes or stop-rotate-go type of movements. Those restriction needs to be taken into consideration when building a mission control system, moreover, the problem increases in complexity when the goal is to fly in formation with several UAVs, indeed during its development, we have to handle also the scalability of the communication link and the robustness of the formation during harsh weather conditions and disturbances. In this research we propose a solution based on a vector field This vector field is computed based on the leader attitude and the followers positions. From the vector field, the follower can calculate the heading and the speed that it has to keep in order to reach the formation. To reach this solution, we first defined a desired heading and ground speed, then, by defining the goals of the UAV and the dynamic of the UAV we found the commanded heading and the commanded ground speed for each follower. The stability of the result is checked by dividing the convergence problem into two smaller problems and applying the Lyapunov stability theory. The solution is fully implemented using state of the art technology in embedded and autopilots for UAV. The system was physically simulated with ROS in Gazebo. At the end, the performances are compared to another state of the art solution, in which VFF outperformed in most of the cases

Understanding the shape of a human foot is a challenge approached by a wide range of disciplines and industries. Traditional methods of obtaining foot measurements are being replaced with newer 3D scanning technologies, obtaining more accurate and repeatable results. However, there is still a lack of insight into the dynamic morphology of human foot during motion. Obtaining an insight into the shape of the foot during motion is possible, but not widely accessible, due to expensive and custom equipment used in existing 4D foot scanning prototypes. This work focuses on developing a 4D foot scanning prototype using commodity hardware, aiming to provide better insight into the dynamic foot morphology and make research in this field more accessible. The prototype is based on RGB-D cameras which offer an affordable access to 4D scanning, using active stereoscopic vision technology.

Space has always been fascinating to humans, since the dawn of civilization. From the first astronomers and philosophers of ancient times, who looked at the night sky searching for answers, to the scientists and engineers of modern missions, commanding space probes to the edge of the solar system, space has always been at the epicenter of scientific discovery and human curiosity. From the launch of Sputnik 1 in 1957, to the robotic rovers exploring Mars, space missions have always relied on the latest technological advancements in order to enable physical or remote exploration of celestial bodies. Traditionally, designing a space computer required significant amount of resources, leading to designs with impressive radiation performance records. However, such designs were lacking computational performance, required years of development and as a result increased the total cost of the mission.

In recent years, the advent of CubeSats meant that access to space became available to a wider community of enthusiasts, researchers and private companies who were developing low-mass spacecraft made out of Commercial Off-The-Shelf components (COTS). These components however, were designed with the goal of maximizing performance and power, with little to no flight heritage. Several novel technologies were proposed in the field of error detection and mitigation, in an effort to bridge the gap between COTS processors and their radiation-hardened counterparts. Even though the commercial semiconductor industry has increased the reliability of its products by continuously improving their designs and processes, CubeSats or other low-mass spacecraft that use these components are still less reliable than their larger counterparts.

Given the aforementioned, this thesis aimed at exploring the latest developments in the field of space embedded systems and error detection techniques, in an effort to produce a software flow able to detect faults with increased compatibility across processor models. In order to accomplish this goal, the thesis was carried out at ARM Limited, as part of the Software Test Libraries (STL) team responsible for developing efficient assembly tests for detecting random faults. The Cortex-M55 CPU was chosen as the test-bed for this work, in order to develop STL routines for a reference module. TheMain Interface Unit (MIU) was chosen to act as the proof-of-concept, since it is an important module in every Cortex-M processor, interfacing the core with the main memory.

More specifically, a series of tests were developed for every major module within the MIU. The design started from the largest module first, which yielded a good trade-off between coverage and time. The tests comprised of efficient assembly routines designed to trigger specific memory access patterns, targeting different portions of logic each time. At the same time, a verification software flow was developed in order to test the newly designed routines against a multitude of possible configurations and initialization parameters. This activity was necessary to ensure that the developed software will be able to operate in a variety of end applications, either in the context of a Real-Time Operating System or baremetal application.

The developed STL tests were subjected to a series of fault simulations using a state-of-the-art hardware simulation tool called ZOIX. Permanent faults caused by accumulated damage were modeled as stuck-at-faults, whereas transient soft-errors were modeled as transient toggle faults. Determining an accurate fault injection interval, required knowledge of the radiation environment that a COTS-based mission would encounter. A state-of-the-art space simulation environment called SPENVIS was used in order to acquire metrics on selected reference missions on Low Earth Orbit and Geosynchronous Equatorial Orbit. This helped setting the upper limits on upset rates, which were in turn used during fault simulation to recreate realistic conditions.

The developed software tests exhibited solid performance in detecting permanent faults, while achieving promising results in transient fault simulations, given certain assumptions. A series of recommendations is given for future research work on the current framework, in an effort to learn from the challenges faced and tackle some of the identified limitations. Given certain assumptions, there is evidence to believe that STLs could be indeed used for random error detection in future CubeSat missions, without increasing the total cost disproportionately.

Annotating a large-scale in-the-wild person re-identification dataset especially of marathon runners is a challenging task. The variations in the scenarios such as camera viewpoints, resolution, occlusion, and illumination make the problem non-trivial. Manually annotating bounding boxes in such large-scale datasets is cost-inefficient. Additionally, due to crowdedness and occlusion in the videos, aligning the identity of runners across multiple disjoint cameras is a challenge. We collected a novel large-scale in-the-wild video dataset of marathon runners. The dataset consists of hours of recording of thousands of runners captured using 42 hand-held smartphone cameras and covering real-world scenarios. Due to the presence of crowdedness and occlusion in the videos, the annotation of runners becomes a challenging task. We propose a new scheme for tackling the challenges in the annotation of such large dataset. Our technique reduces the overall cost of annotation in terms of time as well as budget. We demonstrate performing fps analysis to reduce the effort and time of annotation. We investigate several annotation methods for efficiently generating tight bounding boxes. Our results prove that interpolating bounding boxes between keyframes is the most efficient method of bounding box generation amongst several other methods and is 3x times faster than the naive baseline method. We introduce a novel way of aligning the identity of runners in disjoint cameras. Our inter-camera alignment tool integrated with the state-of-the-art person re-id system proves to be sufficient and effective in the alignment of the runners across multiple cameras with non-overlapping views. Our proposed framework of annotation reduces the annotation cost of the dataset by a factor of 16x, also effectively aligning 93.64\% of the runners in the cross-camera setting.

Many people worldwide suffer from epileptic seizures and not all of them can be prevented using medicines, this thesis is being done for seizure prevention. This is based on implementing a medical body area network (MBAN) that takes sensory recordings across the whole body. This is needed as the research group that proposes this project found from previous research that this is needed for timely seizure prevention. In this report the design, implementation and results of building a prototype MBAN using Bluetooth low energy (BLE) is discussed. The result is a prototype that can measure heart rate when Bluetooth is turned off, but does function with Bluetooth when the heart rate sensor is replaced with mock data. Recommendations are made as to how to resolve the issues that arose during the implementation and as to which topologies should be implemented in the future.

This project was commissioned by the department of neuroscience at Erasmus MC to help future research and on epilepsy and potentially develop a reliable way of prevention some seizures. In this project a Medical Body Area Network is proposed to accomplish this. With the MBAN proposed it will be possible to safely and securely collect data from sensor nodes on the body. Different methods will be discussed for this to be achieved and a prototype will be made.

Underwater robots are widely used in various operations below the surface of the sea. In many of these operations the precise localization and positioning is quite important, especially in cases that the robot must navigate between man-made installations. Although underwater vehicles can carry a number of different sensors, many of them can not be exploited for efficient navigation, due to costs, complexity, weight and inaccuracy. Most of robots feature at least one camera, a sensor that can be cheap, small, with low power requirements and that offers vast amount of information. The advances in computer vision and embedded systems have set cameras as an attractive mean for navigation. This combination allows computer vision as a viable alternative to provide data in real-time. This data can be used locally as a positioning source for the own robot control system, or to inform the navigation coordinates to an observer
or another system. Visual Odometry (VO) is the process of estimating the position and orientation of a robot based completely on data acquired by cameras. The camera-only system can be enhanced with the fusion of an Inertial Measurement Unit (IMU) to estimate motion even more accurately, resulting in Visual Inertial Odometry (VIO). This thesis researches various approaches for underwater navigation with edge computing and focuses on systems that utilize a camera and an IMU. A VIO system architecture is proposed, comprised by a machine vision camera, an IMU, a micro-controller and the embedded system Jetson Xavier from NVIDIA. Some of the most recent VO/VIO algorithms are evaluated on a number of underwater datasets and the impact of the IMU on their performance is assessed. Design issues are discussed and challenges related to the camera - IMU fusion are analyzed. The Visual-Inertial ORB-SLAM (ORB-SLAM + IMU) algorithm is deployed on the proposed VIO system and is optimized on the embedded GPU. The whole framework is evaluated on an artificial underwater structured environment which was created in an indoor tank. While the outcome of the algorithm on motion estimation is examined, the computational performance of the embedded system is profiled for various power modes as well. Results show that the proposed VIO system is able to estimate the underwater robot’s traversed trajectory in the tank with adequate accuracy and that can execute the Visual-Inertial ORB-SLAM in real-time with sufficient speed.