The Self-Driving Car Engineer is an online certification intended to prepare students to become self-driving car engineers. The program was developed by Udacity in partnership with Mercedes-Benz, NVIDIA, Otto, DiDi, BMW, McLaren and NextEv.
In this project, a kalman filter is utilized to estimate the state of a moving object of interest with noisy lidar and radar measurements.
In this project, an Unscented Kalman Filter is utilized to estimate the state of a moving object of interest with noisy lidar and radar measurements.
The robot has been kidnapped and transported to a new location! Luckily it has a map of this location, a (noisy) GPS estimate of its initial location, and lots of (noisy) sensor and control data. In this project, a 2 dimensional particle filter is implemented in C++. The particle filter will be given a map and some initial localization information (analogous to what a GPS would provide). At each time step, the filter will also get observation and control data.
The proportional–integral–derivative controller is implemented to steer the car.
The Model predictive control is implemented to steer the car.