Improving a stereo-based visual odometry prototype with global optimization

In this degree project global optimization methods, for a previously developedsoftwareprototype of a stereo odometry system, were studied. The existing softwareestimatesthe motion between stereo frames and builds up a map of selected stereo frameswhich accumulates increasing error over time. The aim of the project was to studymethods to mitigate the error accumulated over time in the step-wise motionestimation.One approach based on relative pose estimates and another approach based onreprojection optimization were implemented and evaluated for the existing platform.The results indicate that optimization based on relative keyframe estimates ispromising for real-time usage. The second strategy based on reprojection of stereotriangulatedpoints proved useful as a refinement step but the relatively small errorreduction comes at an increased computational cost. Therefore, this approachrequiresfurther improvements to become applicable in situations where corrections areneededin real-time, and it is hard to justify the increased computations for the relatively smallerror reduction.The results also show that the global optimization primarily improves the absolutetrajectory error