CMOS Hall sensors consist of current-biased n-well plates that output magnetic-field dependent voltages. Offsets due to n-well inhomogeneity can then be suppressed by the spinning-current technique, which involves periodically rotating the direction of the biasing current and averaging the resulting output voltages. However, its effectiveness is limited by the JFET effect, which refers to the formation of a depletion region between the n-well and the p-type substrate due to the voltage drop across the n-well. This depletion region modulates the n-well resistance, and so is also a source of residual offset.

In this work, a CMOS Hall sensor is reported which employs voltage biasing and reads out the short-circuit Hall current. Compared to current biasing, this stabilizes the voltage drop across the n-well and significantly reduces the offset due to the JFET effect. Implemented in a standard 180nm CMOS process, the resulting sensor achieves a 3σ offset of 1.1μT with a noise floor of 60nT/√Hz. Compared to the state-of-the-art, these results represent a 3x reduction in offset, and a 5x improvement in resolution.

Thermoelectric generators (TEGs) are critical in environments where alternative energy harvesting methods are necessary, such as space exploration. This thesis investigates using a two-dimensional hole gas (2DHG) as a p-type material within a Gallium Nitride (GaN) based TEG. This study focuses on determining the thermoelectric performance of the 2DHG by measuring the Seebeck coefficient, electrical conductivity, and power factor for extremely cold environments.

This work introduces a novel simulation method used to evaluate different structures to find the optimal hole densities for maximizing the power factor (PF) of the 2DHG. A structure was realized, and its thermoelectric properties were experimentally assessed. Key results, including a Seebeck coefficient of 100 − 200 μV /∆K, a sheet resistance of 70 − 120 kΩ , and a resulting Power Factor (PF) of 60 − 100 μW m−1K−2, are measured over an extremely low-temperature range of 50 - 300 Kelvin and discussed for future applications.

These results demonstrate that GaN-based TEGs can significantly broaden the temperature range and improve the performance of TEGs in extreme conditions. These findings pave the way for more efficient thermoelectric systems, with potential applications in aerospace, deep-space missions, and other challenging environments.

The goal of this thesis is to develop a ROS package that facilitates the control and navigation of a Duckiebot robot. With the rise of robot swarms the need for autonomous charging system for robots is increasing. An implementation for decentralised autonomous behaviour for a Duckiebot for a wireless charging system in a Duckietown environment is discussed. The devised system is divided among three different modules and is implemented in ROS:
• An image recognition module;
• A navigation module;
• A motion control module;
The image recognition module uses linear image processing techniques and YOLO object detection in order to detect objects in images from the robots front facing camera. It detects traffic lights and road markings in order to tell the robot where to go.

The navigation module uses odometry to keep track of the robots current position. The odometry is reset in order to maintain accuracy. When the battery of the robot reaches a certain point the robot will decide to
charge. It will then initiate path finding using Lee’s algorithm in order to find a path to a charging park.

Finally the motion control processes all the information in order to drive the wheels of the robot.
The system is thought to be able to navigate to a charging station, charge and then leave the charging station using the designed ROS package.