Stereo Visual Inertial Odometry for Robots with Limited Computational Resources
Stavrow Bahnam,Sven Pfeiffer,Guido C.H.E. de Croon,Stavrow Bahnam,Sven Pfeiffer,Guido C.H.E. de Croon
Current existing stereo visual odometry algorithms are computationally too expensive for robots with restricted resources. Executing these algorithms on such robots leads to a low frame rate and unacceptable decay in accuracy. We modify S-MSCKF, one of the most computationally efficient stereo Visual Inertial Odometry (VIO) algorithm, to improve its speed and accuracy when tracking low numbers of ...
