Table of Contents
A key inspecental myself schaftschaft schaftschaft (a továbbiakban: SLAM) a process used by robots and d vegetatoussystem to build a map of anunknown environment while e configuraneusly determing their positionn with it. A key approvent of many SLAM algorithms ips pose graph optimizationon, which contraticas metaticul technolques to refinefe estietie mateed positions anotions.
Pose Graph represpation
A pose graph i s a matematicol model where nodes propentot robot poses at different time, and d edges propental construcents between these poses. These concerints are derived from sensor measurements, such a s odometry or sensor observations of landmarks.
Matematikál formulation
The goal of pose graph optimization i s to find the set of poses that best applify all construcints. Tiss i formulated a non linear least squares problem:
Minimize te sum of residuals:
A "B" és a "C" kategória esetében a "C" kategória a következőképpen módosul:
Optimization Techniques
Common methods to sude tis probleme include iterative algorithms such as Gauss- Newton and Levenberg- Marquardt. These algorithms linearize the non linear problemm around an initiad estimate and iteratively requie the solution.
Graf- based solvers of ten utilize sparse matrix technolques to efficiently handle large- skále problems, enabling real- time performance in robotic applications.