Autonomous Navigation with ROS Navigation Stack
This technical presentation provides a complete walkthrough of a custom autonomous navigation stack developed for a differential-drive mobile robot using ROS Noetic. The presentation covers robot kinematics, sensor integration, and software architecture for a robotic platform equipped with a 360° LiDAR, Intel RealSense D435 RGB-D camera, BNO055 9-DOF IMU, and wheel encoders.
Topics include Extended Kalman Filter-based odometry fusion, RTAB-Map visual-inertial SLAM, AMCL particle-filter localization, map generation, and deployment of the ROS1 Navigation Stack for fully autonomous navigation within a known environment. The presentation emphasizes practical implementation details and system integration challenges encountered during development.
6th-Year Ph.D. Student in Electrical Engineering with a concentration in Robotics & Autonomous Systems at the University of Central Florida.
🎓 Expected Graduation: Summer 2027
🔬 Research Identity: Learning-Based State Estimation and Control of Uncertain Dynamical Systems