In this article, we present a framework for model-free batch localization and simultaneous
localization and mapping (SLAM). We use lifting functions to map a control-affine system into …

With the rapid development of microelectromechanical systems (MEMS), smartphones
become one of the most convenient tools to realize pedestrian positioning during daily life …

With the recent influx in demand for multi-robot systems throughout industry and academia,
there is an increasing need for faster, robust, and generalizable path planning algorithms …

We propose a manifold optimization approach for solving constrained inference and
planning problems. The approach employs a framework that transforms an arbitrary …

Factor graphs are a very powerful graphical representation, used to model many problems
in robotics. They are widely spread in the areas of Simultaneous Localization and Mapping …

Robot motion planning via probabilistic inference renders a unique viewpoint on the
trajectory optimization problem, in which the joint distribution of motion objectives is …

The execution of flight missions by unmanned aerial vehicles (UAV) primarily relies on
navigation. In particular, the navigation pipeline has traditionally been divided into …

LiDAR odometry is essential for many robotics applications, including 3D mapping,
navigation, and simultaneous localization and mapping. LiDAR odometry systems are …

Unmanned aerial vehicles (UAV) showed great potential in improving the efficiency of parcel
delivery applications in the coming smart cities era. Unfortunately, the trustworthy positioning …

Simultaneous localization and mapping (SLAM) is applicable in robotics and mobile
platforms. SLAM approaches empower robots to create intricate maps of their surroundings …