Autonomous Perception & LiDAR Visualization

Tech Stack: ROS 2, RViz2, Linux (Ubuntu), Point Cloud Data, KITTI Dataset

Overview

Developed a simulation environment to process and visualize high-density LiDAR point clouds and camera feeds for autonomous vehicle perception.

Key Implementations

• Replayed and analyzed complex .mcap sensor data from the KITTI Vision Benchmark Suite using ROS 2.
• Configured RViz2 to synchronize multi-sensor streams, overlaying 3D LiDAR point clouds with real-time 2D camera feeds to simulate real-world autonomous navigation.
• Handled spatial transforms (TF) and simulated clock synchronization to ensure accurate playback of multi-modal environmental data.