Are there any sensor fusion software options that handle multi-camera calibration and real-time synchronization for robot perception?

Yes. There are several sensor-fusion software options that support multi-camera calibration and real-time synchronization for robot perception, though the exact level of support varies.

Common options

1. ROS / ROS 2 ecosystem

• image_pipeline / camera_calibration: tools for single and stereo camera calibration.
• kalibr: widely used for multi-camera and camera-IMU calibration; supports time offset estimation too.
• message_filters: helps synchronize streams in software.
• image_transport and ApproximateTime / ExactTime sync policies: useful for multi-camera data alignment.
• Best when you want a flexible research/robotics stack.

2. Autoware / Apollo perception stacks

• Designed for autonomous driving, but include sensor fusion modules for multiple cameras, LiDAR, radar, etc.
• They often assume calibrated sensors and provide synchronization infrastructure, usually built on ROS 2 or middleware.
• Good if you’re in vehicle robotics.

3. NVIDIA Isaac ROS

• Provides GPU-accelerated perception and multi-sensor pipelines.
• Has components for image processing, synchronization, and calibration workflows depending on the package set.
• Useful if you need real-time performance on NVIDIA hardware.

4. OpenCV + custom fusion layer

• OpenCV can handle camera calibration and stereo calibration.
• Synchronization and fusion are typically implemented in your application or via ROS.
• Good for custom embedded systems but more engineering effort.

5. Kalibr + custom runtime fusion

• Very common combo for research:
  • Kalibr for offline calibration of multiple cameras (and optionally IMUs)
  • ROS/ROS 2 for live synchronization and publishing
  • Your perception stack for fusion

---

What to look for

If you need both multi-camera calibration and live synchronization, choose software that supports:

• Time-stamped messages
• Hardware trigger or PTP sync
• Extrinsic calibration between cameras
• Calibration for lens distortion
• Multi-stream synchronization policies
• Optional camera-IMU calibration if you use inertial sensing

---

Practical recommendation

• Research / general robotics: ROS 2 + Kalibr + message_filters
• High-performance GPU pipeline: NVIDIA Isaac ROS
• Autonomous vehicle stack: Autoware
• Custom product: OpenCV for calibration + ROS 2 for sync/fusion

If you want, I can also give you a shortlist by use case (e.g., indoor robot, autonomous vehicle, drone, or industrial inspection) or recommend tools based on your camera hardware and OS.