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Showing result 1 - 5 of 56 essays matching the above criteria.

  1. 1. Local traversability assessment in an unmanned ground vehicle : An analysis of mobility on the UGV Husky

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Kidus Y. Getahun; [2023]
    Keywords : UGV; Husky; Robotics Operating System; Traversability Estimation; Vehicle Dynamics; Elevation Mapping; UGV; Husky; Framkomlighets Bedömning; Fordonsdynamik;

    Abstract : This thesis project aims to learn and understand more about implementing a path planner to the unmanned ground vehicle (UGV), UGV Husky, specifically its traversability algorithm, and investigate how it could be further improved. A surrounding grid is generated around the UGV where each cell contains information connected to its traversability. READ MORE

  2. 2. Flood Simulation in the Colombian Andean Region Using UAV-based LiDAR : Minor Field Study in Colombia

    University essay from KTH/Skolan för industriell teknik och management (ITM)

    Author : Simon Höglund; Linus Rodin; [2023]
    Keywords : UAV; Unmanned aerial vehicle; LiDAR; Light detection and ranging; UAV-based LiDAR; UAV photogrammetry; Aerial photogrammetry; Flooding Colombia; UN Sustainability Development Goals; UAV; Obemannade flygfordon; LiDAR; Ljus- och avståndsdetektion; UAV-baserad LiDAR; UAV-fotogrammetri; Flygfotogrammetri; Översvämning Colombia; FN; hållbarhetsutvecklingsmål;

    Abstract : Flooding is a worldwide problem that every year causes substantial damage for the environment and stakeholders nearby, and this impact relates to several of the United Nations Sustainable Development Goals. Colombia is specially prone to flooding as 17% of its surface area is at risk of extreme flooding. READ MORE

  3. 3. The influence of soil modeling on the prediction of vehicle dynamics and mobility – A comparison between the Finite Element Method and a Semi[1]Empirical Model

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Jimmy Kjellqvist; [2023]
    Keywords : ;

    Abstract : This master's thesis investigated the influence of soil modeling on vehicle dynamics and mobility predictions with a focus on two different soil models implemented in Project Chrono: the Bekker-Wong model, and a Finite Element (FE) model. The primary objective is to provide insights for decision-making regarding the most suitable soil model under specific circumstances. READ MORE

  4. 4. Data Harvesting and Path Planning in UAV-aided Internet-of-Things Wireless Networks with Reinforcement Learning : KTH Thesis Report

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Yuming Zhang; [2023]
    Keywords : Unmanned aerial vehicle; the Internet of Things; data harvesting; obstacle avoidance; path planning; deep reinforcement learning; Obemannat luftfordon; sakernas internet; datainsamling; undvikande av hinder; vägplanering; djup förstärkningsinlärning;

    Abstract : In recent years, Unmanned aerial vehicles (UAVs) have developed rapidly due to advances in aerospace technology, and wireless communication systems. As a result of their versatility, cost-effectiveness, and flexibility of deployment, UAVs have been developed to accomplish a variety of large and complex tasks without terrain restrictions, such as battlefield operations, search and rescue under disaster conditions, monitoring, etc. READ MORE

  5. 5. Machine Learning on Terrain Data and Logged Vehicle Data to Gain Insights into Operating Conditions for an Articulated Hauler : Machine Learning on Terrain Data and Logged Vehicle Data to Gain Insights into Operating Conditions for an Articulated Hauler

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Tianren Sun; Yen Chieh Wang; [2022]
    Keywords : CNN; Data Driven Manufacturing; Microsoft Azure Maps; Machine; Learning ML ; Road Surface; Topography;

    Abstract : Manufacturers can develop next-generation production and service for their customers by the data gathered and analyzed from customers’ usage conditions. In this research, the operating condition of articular haulers is collected and analyzed through machine learning algorithms to predict the type of operational topographies and road surface. READ MORE