Simultaneous localization and mapping (SLAM) is a fundamental problem for various
applications. For indoor environments, planes are predominant features that are less …

Visual odometry algorithms tend to degrade when facing low-textured scenes—from eg
human-made environments—, where it is often difficult to find a sufficient number of point …

Mixed reality (MR) enables a novel way to visualize virtual objects on real scenarios
considering physical constraints. This technology arises with other significant advances in …

The autonomous navigation of unmanned vehicles in GPS denied environments is an
incredibly challenging task. Because cameras are low in price, obtain rich information, and …

To solve the illumination sensitivity problems of mobile ground equipment, an enhanced
visual SLAM algorithm based on the sparse direct method was proposed in this paper …

Visual sensors have characteristics that make them interesting as sources of information for
any process or system. On the one hand, they are able to capture a very precise and high …

Most RGB-D-based SLAM methods assume texture-rich environments, making them
susceptible to significant tracking errors or complete failures in the absence of texture …

This paper presents two novel solutions to compute motion transformation by effectively
addressing the nonlinear constraints formed by observational data. These solutions have …

In most human made scenes, such as high‐rise urban city or indoor environment, the
surface normal vectors or direction vectors are concentrated in three orthogonal principal …

RGB-D cameras serve as indispensable sensors for indoor simultaneous localization and
mapping (SLAM) in lightweight robots. However, many RGB-D SLAM systems fail to …