What is the ISAM algorithm?

What is the ISAM algorithm, and what does it stand for? The ISAM algorithm, short for Incremental Smoothing And Mapping, is a highly efficient tool in the realm of robotics and computer vision. Developed by researchers such as Michael Kaess and Frank Dellaert, ISAM provides both batch and incremental optimization algorithms that are specifically designed to tackle sparse nonlinear problems encountered in Simultaneous Localization and Mapping (SLAM). ISAM's primary objective is to recover precise minimum least-squares solutions, making it a vital component in applications ranging from 2D and 3D SLAM to complex navigation tasks for mobile robots. By leveraging incremental smoothing techniques, ISAM is able to continuously refine its map estimates as new data arrives, enabling real-time operation and adaptation in dynamic environments. Key features of the ISAM algorithm include its scalability, robustness, and flexibility, allowing it to be easily extended to new problem domains. Its successful deployment in various robotic platforms, including ground robots, aerial vehicles, and underwater robots, underscores its practical relevance and effectiveness in real-world scenarios. In summary, the ISAM algorithm represents a pioneering approach to solving complex optimization problems in robotics and computer vision, enabling precise and efficient navigation and mapping capabilities.