In the development of autonomous vehicles, replacing the driver and its perceptive abilities is one of many technical challenges. As a part in solving these challenges, Light Detection And Ranging (LiDAR) is a promising technology. In short, LiDAR works by using lasers to detect objects in its vicinity by detecting the light that reflects on them. With knowledge of the reflective properties of an object, a prediction can be made regarding whether a certain LiDAR unit will be able to detect the object or not. When making this prediction, the common description of reflectance is often insufficient. Instead, a more complete description is given by the Bidirectional Reflectance Distribution Function (BRDF) of a surface, which describes reflection on the surface while taking the incident and reflected direction into consideration. In this thesis, an experimental setup was built with the capabilities of measuring the BRDF while taking incident and reflected polarization into account. Program software was written in Python and integrated with the hardware, providing a user interface for simple control of the setup. The BRDF was measured on a total of 6 samples; 2 reference samples and 4 samples taken from the hood of 4 different cars. Conclusively, the setup provided useful information about the reflective and polarization properties of the samples. These measurements can help in predicting whether or not a surface can be detected by a given LiDAR unit, and can also be helpful when designing new LiDAR units by providing useful information about the surfaces they are required to detect.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-173469 |
| Date | January 2020 |
| Creators | Tonvall, Daniel |
| Publisher | Umeå universitet, Institutionen för fysik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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