robot-perception

Build a robot perception pipeline by configuring sensor setups, performing calibration, and orchestrating multi-sensor fusion. This process integrates cameras, LiDARs, depth sensors, and IMUs across ROS1 and ROS2 environments for deployment-ready systems.

Multi-sensor calibration involves computing intrinsic, extrinsic, and hand-eye parameters to align cameras, LiDARs, and IMUs. This ensures accurate spatial synchronization and reliable data fusion for robotic perception pipelines.

Manage real-time streaming and latency by orchestrating perception pipelines that handle multi-sensor synchronization. This process ensures low-latency data processing and accurate temporal alignment across ROS1 and ROS2 stacks.

Yes, the perception pipeline supports object detection, segmentation, and tracking for robotic systems. It integrates computer vision and sensor fusion techniques to identify and track objects in real-time.

Yes, the pipeline integrates OpenCV and PCL for vendor-agnostic data processing. This allows you to process sensor data from cameras and LiDARs uniformly, ensuring compatibility across different hardware vendors in ROS environments.