dc.contributor.author | Muyinza, Sophia Sentamu | |
dc.contributor.author | Watala, Alexandar Mark | |
dc.contributor.author | Kiwalabye, Benjamin | |
dc.contributor.author | kawuuma, Joel Joseph | |
dc.date.accessioned | 2024-01-18T13:16:25Z | |
dc.date.available | 2024-01-18T13:16:25Z | |
dc.date.issued | 2023 | |
dc.identifier.citation | Muyinza, S.S.(2019) Lidar sensor for autonomous vehicle (Unpublished dissertation). Kampala: Makerere University | en_US |
dc.identifier.uri | http://hdl.handle.net/20.500.12281/18307 | |
dc.description | A project report submitted to the School of Computing and Informatics Technology for the study leading to a project report in partial fulfilment of the requirements for the award of the Degree of Bachelor of Science in Computer Science of Makerere University | en_US |
dc.description.abstract | This project proposes the development of a micro drone equipped with a Light Detection and Ranging (Lidar) sensor, aimed at detecting unintended obstacles in indoor environments and air. The proposed solutions intend too overcome the limitations of current micro drones' sensing capabilities, enabling them to detect unintended obstacles that are not within their line of sight or that may be obscured by other objects. The drone will use the LiDAR sensor to create a 3D map of the surrounding environment, which will be analysed in real-time using machine learning algorithms to identify potential obstacles. The system will alert the drone operator of any detected obstacles, allowing for timely and safe navigation. The prosed micro drone solution offers potential benefits in various fields, including search and rescue operations, inspection of hard-to-reach areas, and exploration in hazardous environments. | en_US |
dc.language.iso | it | en_US |
dc.publisher | Makerere University | en_US |
dc.subject | Light Detection and Ranging (LiDAR) | en_US |
dc.subject | micro drones’ sensing | en_US |
dc.title | Micro drone with proximity alert system using lidar | en_US |
dc.type | Thesis | en_US |