Sensor integration into autonomous ( model sized) vehicles.
| dc.contributor.advisor | Kovács, László | |
| dc.contributor.author | Boudjadja, Mehdi | |
| dc.contributor.department | DE--Informatikai Kar | hu_HU |
| dc.date.accessioned | 2021-05-05T09:49:42Z | |
| dc.date.available | 2021-05-05T09:49:42Z | |
| dc.date.created | 2021-05-04 | |
| dc.description.abstract | regarding my thesis, i did a research to show that many parts of today's vehicle's dynamic well-being system (e.g. collision avoidance system, road holding system, vulnerable hip detection, universal motion control) can form the basis of autonomous vehicle design. In this current work, we are using sensor fusion, in which LIDAR, an advanced camera, and an ultrasonic distance sensor are used to combine multiple sensors to gradually differentiate objects. Also, Zhang's camera setup method does not require motion data when the camera or plane example moves parallel to each other. The perception block gets the data from sensor devices and combines that data into a piece of meaningful information. Examination of the presented arachnid diagrams shows that there is no ideal sensor, so it is important to combine sensors using explicit algorithms that allow for the attenuation of deformations of each sensor and consolidate their advantages. | hu_HU |
| dc.description.course | Computer Science BSc | hu_HU |
| dc.description.degree | BSc/BA | hu_HU |
| dc.format.extent | 57 | hu_HU |
| dc.identifier.uri | http://hdl.handle.net/2437/308502 | |
| dc.language.iso | en | hu_HU |
| dc.subject | Camera | hu_HU |
| dc.subject | Radar | hu_HU |
| dc.subject | GPS | hu_HU |
| dc.subject | IMU | hu_HU |
| dc.subject | sensors | hu_HU |
| dc.subject | Autonomous | hu_HU |
| dc.subject | Vehicles systems | hu_HU |
| dc.subject | Sensor fusion | hu_HU |
| dc.subject | Machine learning | hu_HU |
| dc.subject | LiDAR | hu_HU |
| dc.subject.dspace | DEENK Témalista::Informatika | hu_HU |
| dc.title | Sensor integration into autonomous ( model sized) vehicles. | hu_HU |