SLAM++ is an implementation of incremental nonlinear least squares solvers, containing lighting fast linear algebra on sparse block matrix operations. It is aimed for the use in 3D reconstruction and SLAM online applications. The code has been exhaustively tested and compared with the existing similar implementations and constitutes the base for more than ten high impact publications.

Comparing to other similar software (g2o, gtsam, isam), SLAM++ is based on an efficient sparse, block matrix data-structure that facilitates numerical and structural changes in the system matrix as well as speeds up matrix arithmetic operations and matrix factorization.  This allowed for very efficient solutions to incremental problems, where the size of the state increases every step as well as for efficient covariance recovery. A comprehensive explanation of the block-matrix manipulation to obtain the covariances is given at:

Author - Robotic Vision

Robotic Vision

The ARC Centre of Excellence for Robotic Vision is leading the world in transformational research tackling the critical and complex challenge of applying computer vision to robotics. We believe that the ability to see, to visually understand the complex world around us and respond to it, is critical for the next generation of robots that will perform useful work in agriculture, environmental monitoring, healthcare, infrastructure inspection, construction and manufacturing. We believe that robotic vision is the key to unleashing the full potential of robots and fundamentally changing the way we live and work. Link

Category: Software
Posted 30 April 2016


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