SELECTED WORKRobotics & simulation
PROJECT NOTE
SLAM & Kalman Localization
Exploring vehicle localization and navigation with noisy sensor readings.
- ROLE
- Filter implementation and obstacle avoidance
- CONTEXT
- Team autonomous-navigation simulation
- YEAR
- 2024
- TOOLS
- ROS2, Webots, Python, LiDAR, Extended Kalman Filter
OVERVIEW
The work behind the system.
A team navigation project in ROS2 and Webots, using a simulated Tesla Model 3 to explore mapping, localization, and obstacle avoidance. I implemented the Kalman-filter node and added LiDAR obstacle avoidance to the camera lane follower.
BUILD NOTES
What I focused on
- 01
Implemented an Extended Kalman Filter for vehicle localization.
- 02
Combined LiDAR and camera data for environmental perception.
- 03
Used simulation to iterate on lane following and obstacle avoidance.
ROS2WebotsPythonLiDARExtended Kalman Filter