@masterthesis{LezanaPascual, type = {Bachelor Thesis}, author = {Lezana Pascual, Miguel}, title = {Development of an Agrivoltaic Plant}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-18536}, school = {Hochschule Rhein-Waal}, pages = {77}, abstract = {The present paper deals with developing two Agrivoltaics (Agri-PV) plants in Kleve, Germany, to study their feasibility and analyze the interaction between cattle farming and solar photovoltaic power generation. The study area will be used as pasture to feed the cows, which will allow evaluation of the economic and technical feasibility of this combination in an area called the "test area" and then to perform the second installation with a larger area called the "potential area." The main results include the decisions taken for the plant's design, the efficiency and performance of the Agri-PV system, the economic results obtained through simulations in PV*SOL software, and the use of plans developed in AutoCAD. The objective of the report is the correct implementation of the Agri-PV system in both the test area and the potential area. It has been demonstrated that integrating solar energy in agricultural areas offers a favorable economic projection, with adequate returns and positive cash flows. This implementation represents an opportunity to diversify income in the farm sector by generating energy for export to the power grid. The conclusions highlight the feasibility of the Agri-PV model and its potential as an effective solution for renewable energy generation in agricultural areas. Further research is suggested to evaluate the impact on agricultural productivity and the interaction of the cows with the panels and to conduct long-term economic and financial studies to ensure the system's sustainability.}, language = {en} } @masterthesis{Usluer2025, type = {Bachelor Thesis}, author = {Usluer, Egehan}, title = {Applying Different Path Planning Algorithms to a Mini Mars Rover for an Uncharted Maze}, url = {http://nbn-resolving.de/urn:nbn:de:hbz:1383-opus4-22775}, school = {Hochschule Rhein-Waal}, pages = {69}, year = {2025}, abstract = {This thesis explores how an already built Mini Mars Rover can autonomously navigate an uncharted maze, first by mapping it and then by applying different pathfinding strategies. The Mini Mars Rover uses IR sensors for wall detection, encoder-based odometry for tracking movement, an IMU for heading corrections, for input for more accurate localization. The strategy combines exploration techniques with practical path execution on real hardware, focusing on the challenges that come up when algorithms meet the physical world. Exploration applied by using a combination of Breadth-First Search (BFS) with the Travelling Salesman Problem (TSP) approach, as well as a Partially Observable Markov Decision Process (POMDP) strategy. Although both methods showed promising results in simulation, in hardware testing same results were not gathered. For the path planning, three pathfinding algorithms Flood Fill, Dijkstra's, and A* are implemented and compared. The results of those algorithms and the strategy to adopt them into the robot is implemented. The project demonstrates a possibility of adaptation of those algorithms and their feasibility. The Mini MarsRover serves as a solid base for further development and improvements.}, language = {en} }