Modeling of a localization sensor of a vehicle with a low cost GPS and proprioceptive sensors

• Grant number: 15/04571-8
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: June 01, 2015
• End date: May 31, 2016
• Field of knowledge: Engineering - Mechanical Engineering - Mechanical Engineering Design
• Principal Investigator: Janito Vaqueiro Ferreira
• Grantee: Larissa Antonelli Santesso
• Host Institution: Faculdade de Engenharia Mecânica (FEM). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil

Abstract

The development in the automobilist robotics area improved in the last years, making the existence of autonomous vehicles possible. However, the technology used in this type of vehicle is expensive, causing its limited access. Hence there is an encouragement in the study of low cost technologies with the purpose of improving its performance in autonomous vehicles. The localization study is one of the areas that must be explored in order to acquire a good result in the vehicle navigation. This project has the objective to obtain a localization estimative closer to the real position and momentary of the vehicle to ensure a precise navigation through the development of a simulated localization method from the validation of a low cost device which is going to be used in the vehicle real platform. In the real platform, it will be used sensors in the wheel (encoders) and an auxiliary equipment, developed by U-blox, which provides a localization estimative by the fusion of data obtained from the reading of sensors included in it (GPS and gyroscope). This combination is performed by a recursive estimator called the Kalman filter. In order to verify this equipment performance, it is intended to develop a virtual sensor in the simulator software (MORSE), which is going to be used, with a similar behavior of the U-blox appliance, once this one is not included in the simulator. Furthermore, other types of sensors, provided by the same software, will be used in the simulated vehicle. With this last stage, the intention is to afford a localization evaluation obtained by other sensors, with the possibility of improving the localization accuracy from the device.