4 accepted papers
Pose graph optimization is a special case of the simultaneous localization and mapping problem where the only variables to be estimated are pose variables and the only measurements are inter-pose constraints. The vast majority of pose graph optimization techniques are vertex based (variables are rob
Accurate robotic state estimation often requires precise knowledge of inter-sensor offsets. In this letter we present a solution for inter-sensor calibration of systems that employ a combination of GNSS and visual-inertial sensors. RTK-GNSS and fiducial measurements are utilized to produce highly pr
This paper presents a method for the robust selection of measurements in a simultaneous localization and mapping (SLAM) framework. Existing methods check consistency or compatibility on a pairwise basis, however many measurement types are not sufficiently constrained in a pairwise scenario to determ…
Pose graph optimization is a common problem in robotics and associated fields. Most commonly, pose graph optimization is performed by finding the set of pose estimates which are the most likely for a given set of measurements. In some situations, arbitrarily large errors in pose graph initialization