Stimulate learning for autonomous vehicles: From building the Kiwi car to implementation of software
| dc.contributor.author | Jansson, Anton | |
| dc.contributor.department | Chalmers tekniska högskola / Institutionen för mekanik och maritima vetenskaper | sv |
| dc.contributor.department | Chalmers University of Technology / Department of Mechanics and Maritime Sciences | en |
| dc.contributor.examiner | Benderius, Ola | |
| dc.contributor.supervisor | Benderius, Ola | |
| dc.date.accessioned | 2023-03-14T16:11:35Z | |
| dc.date.available | 2023-03-14T16:11:35Z | |
| dc.date.issued | 2021 | |
| dc.date.submitted | 2023 | |
| dc.description.abstract | In this thesis, the so called Kiwi platform was studied as a tool for teaching au tonomous systems and OpenDLV to four target groups: secondary education, un dergraduate education, postgraduate education, and hobbyists. The Kiwi platform consists of a 3D printed car equipped with sensors for measuring distances as well as a camera for image processing. Moreover, the open source software environment OpenDLV, was used to develop and test algorithms for driving the Kiwi car autonomously. The project was divided into two main parts, starting with building the Kiwi car and then programming it. Afterwards a survey was conducted in order to evaluate this teaching concept. Only one test group was involved in building the car, while all groups programmed it. In order to build the car, the primary resource was step by step instructions. When programming the car, the test groups were given a selection of mandatory topics. The steps were presented both in text as well as with video tutorials. Based on the results from the survey the participants found the tutorials relevant and extensive enough for the four programming tasks. Having said that, only the two test groups with the expected highest prior knowledge completed all the tasks in time, which may indicate that the tutorials may have been to advanced. Furthermore, the negative feedback from the survey were regarding the more technically challenging sections. The test groups with highest expected prior knowledge found that the material as a simplification of their intent, this was not expressed by the other test groups. Regarding the user manual for building the Kiwi car, the data was not extensive enough to draw any general conclusions. | |
| dc.identifier.coursecode | MMSX30 | |
| dc.identifier.uri | http://hdl.handle.net/20.500.12380/306007 | |
| dc.language.iso | eng | |
| dc.relation.ispartofseries | 2021:74 | |
| dc.setspec.uppsok | Technology | |
| dc.subject | programming | |
| dc.subject | Kiwi car | |
| dc.subject | autonomous driving | |
| dc.subject | teaching | |
| dc.subject | online community | |
| dc.title | Stimulate learning for autonomous vehicles: From building the Kiwi car to implementation of software | |
| dc.type.degree | Examensarbete för masterexamen | sv |
| dc.type.degree | Master's Thesis | en |
| dc.type.uppsok | H | |
| local.programme | Complex adaptive systems (MPCAS), MSc |