Interfacing and testing of localization sensors on an autonomous vehicle
There has been an increasing demand for the usage of autonomous (also called self-driving, driver-less or robotic) capabilities in electric vehicles all over the world. Autonomous Vehicle (AV) technology has potential to improve mobility and smart transportation, and it can contribute to enhancement...
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Format: | Final Year Project |
Language: | English |
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Nanyang Technological University
2020
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Online Access: | https://hdl.handle.net/10356/136704 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | There has been an increasing demand for the usage of autonomous (also called self-driving, driver-less or robotic) capabilities in electric vehicles all over the world. Autonomous Vehicle (AV) technology has potential to improve mobility and smart transportation, and it can contribute to enhancement of our life. AVs require precise knowledge of position and orientation for Self-Localization, Perception, and Path Planning. AVs carry multiple sensors, including GPS, IMU, LIDAR, RADAR and on-board computers. Localization is an essential component of AVs. AVs usually drive autonomously using a precise map. AVs could follow way points using precise location, and they can identify the safe spots to complete the required mission. In addition, real-time pose estimation (position and attitude) is a key function for AVs on the road. This final year project successfully explores AV localization. The report gives an overview for global positioning and relative localization based on the local map. Another objective of the project is the integration of localization sensors e.g. GPS, LIDAR and RADAR. These technologies needed to work together with the existing Autoware software system in Toyota COMS EV. Furthermore, one of the objectives of the project is the incorporation of the localization outputs, in real-time, as the input for way-point generation system, in order to make the Toyota COMS EV drive autonomously. Lastly, one of the objectives of the project is to apply the algorithms to detect and avoid obstacles during the low speed autonomous mode. |
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