cocel-postech/genz-icp

What it solves

GenZ-ICP addresses the problem of LiDAR odometry instability in "degenerate" environments—areas where the sensor data lacks sufficient geometric features to accurately determine movement (e.g., long corridors or open plains). It aims to provide a generalizable and robust way to estimate a robot's trajectory without failing in these feature-poor zones.

How it works

The system implements a LiDAR odometry pipeline using an adaptive weighting mechanism. This allows the algorithm to dynamically adjust how it processes sensor data to maintain accuracy and robustness against degeneracy, ensuring the robot can track its position even when the surrounding environment provides limited geometric information.

Who it’s for

This tool is designed for robotics researchers and engineers working on SLAM (Simultaneous Localization and Mapping) and localization, specifically those using LiDAR sensors on autonomous vehicles or mobile robots.

Highlights

• Degeneracy-Robust: Specifically designed to handle environments where traditional ICP (Iterative Closest Point) methods often fail.
• Multi-Language Support: Available in both C++ and Python implementations.
• ROS Integration: Full support for both ROS 1 and ROS 2, making it easy to integrate into existing robotic software stacks.
• C++ and Python: Offers a pip-installable Python package for rapid prototyping and a C++ version for high-performance production use.