Robust Visual SLAM and Path Planning for Autonomous Vehicles in Outdoor Environments

This project developed a robust visual SLAM and path planning system for autonomous vehicles in complex outdoor environments. We integrated GPS data with visual SLAM to enhance accuracy and efficiency, and created a path planning algorithm considering road stability and driving time. My role focused on hardware setup, sensor integration, and data acquisition. I configured the autonomous vehicle’s sensor systems, developed methods for multi-sensor data collection and processing, and assisted in robot construction with emphasis on optimal sensor placement. This research significantly advances autonomous navigation capabilities in areas where traditional mapping methods are ineffective, such as dense forests.