Evaluating SLAM / VIO Systems for UAV Use

Problem definition

Which open-source SLAM or VIO system should I evaluate first for my UAV's sensors, compute and mission profile?

Steps

1. Record sensor assumptions

   Open each candidate repository and record the required sensors: monocular, stereo, RGB-D, LiDAR or IMU. A LiDAR SLAM system is not interchangeable with a visual one.

2. Check the license and maintenance signal

   Record the SPDX license from the official API and the last activity/archive flag. Unknown licenses stay Unknown.

3. Run the documented dataset

   Run each estimator on the dataset its official documentation recommends before any hardware work. Record the version you used.

4. Estimate compute footprint

   Check the official README for compute requirements and compare them with your onboard hardware before adoption.

5. Verify integration path

   Confirm whether the system ships ROS/ROS 2 interfaces or a documented API for your flight stack.

Guide

Judgment criteria

• The system runs on its documented dataset with the recorded sensors.
• License, maintenance and compute assumptions are recorded before integration.

Common risks

• Treating a LiDAR SLAM result as evidence for a visual pipeline.
• Skipping the sensor-assumption check and pairing an incompatible estimator with your vehicle.

Checklist