Mobile Robot Docking Simulation | RANSAC Feature Detection Under Harsh Disturbances скачать в хорошем качестве

Mobile Robot Docking Simulation | RANSAC Feature Detection Under Harsh Disturbances

This video demonstrates a simulated mobile robot docking system developed using LiDAR-based feature detection with RANSAC. The docking controller performs geometry-based pose estimation and closed-loop alignment in simulation, and is tested under harsh disturbance conditions including injected pose noise and localization perturbations. The objective was to evaluate robustness against sensor noise and state estimation errors, ensuring reliable docking performance under non-ideal conditions. This project was developed as part of a technical interview assessment for Certis. Key components: 1. LiDAR feature extraction and RANSAC-based corner detection 2. Relative pose estimation in robot frame 3. Closed-loop docking controller with yaw alignment 4. Disturbance testing via pose noise injection Environment: Ubuntu 22.04 + ROS2 Humble Gazebo Classic Link to Github: https://github.com/PiusLim373/robust_...