4 accepted papers
This paper proposes a simple yet effective approach to learn visual features online for improving loop-closure detection and place recognition, based on bag-of-words frameworks. The approach learns a codeword in the bag-of-words model from a pair of matched features from two consecutive frames, such
Not all measured features in SLAM/SfM contribute to accurate localization during the estimation process, thus it is sensible to utilize only those that do. This paper describes a method for selecting a subset of features that are of high utility for localization in the SLAM/SfM estimation process.…
The scales on the skin of a snake are an integral part of the snake's locomotive capabilities. It stands to reason that the integration of scales into the design of robotic snakes would open new properties to exploit. In this work, we present a robotic snake design that incorporates rigid scales in…
This paper utilizes system observability to guide monocular SLAM. Instead of providing all measured features then performing data-driven outlier rejection (such as with RANSAC), we propose to identify only the minimal subset of features which form an optimally observable SLAM subsystem for localizat…