A convex optimization based approach for pose SLAM problems
DSDP implements the dual-scaling algorithm for semidefinite programming. The source code if this interior-point solver, written entirely in ANSI C, is freely available. The solver can be used as a subroutine library, as a function within the MATLAB environment, or as an executable that reads and writes to files. Initiated in 1997, DSDP has developed into an efficient and robust general purpose solver for semidefinite programming. Although the solver is written with semidefinite programming in mind, it can also be used for linear programming and other constraint cones. The features of DSDP include: • a robust algorithm with a convergence proof and polynomially bounded complexity under mild assumptions on the data, • primal and dual solutions, • feasible solutions when they exist or approximate certificates of infeasibity, • initial points that can be feasible or infeasible, • relatively low memory requirements for an interior-point method, • sparse and low-rank data structures, • extensibility that allows applications to customize the solver and improve its performance, • a subroutine library that enables it to be linked to larger applications, • scalable performance for large problems on parallel architectures, and • a well documented interface and examples of its use. The package has been used in many applications and tested for efficiency, robustness, and ease of use. We welcome and encourage further use under the terms of the license included in the distribution.