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Lidar-Odometry and Mapping (LOAM)
- A re-implementation of one of the top ranked Visual Odometry/SLAM algorithms on the KITTI odometry benchmark suite. The original author is Ji Zhang from CMU. I was personally interested in this algorithm because it takes a unique, optimization based approach to point cloud registration. Additionally, this algorithm does not support loop closure yet outperforms other state-of-the-art SLAM methods. This ended up as my final project for EECS 568: Mobile Robotics, where I applied skills such as git, ROS, C++, nonlinear optimization (Levenberg–Marquardt), SLAM (Simultaneous Localization and Mapping), and ICP (Iterative Closest Point).
- C++ ROS KITTI Github
