Moving towards autonomy, unmanned vehicles rely heavily on state-of-the-art collision
avoidance systems (CAS). A lot of work is being done to make the CAS as safe and reliable …

Simultaneous localization and mapping (SLAM) technology is essential for robots to
navigate unfamiliar environments. It utilizes the sensors the robot carries to answer the …

Here, we present a general framework for combining visual odometry and lidar odometry in
a fundamental and first principle method. The method shows improvements in performance …

We present a data processing pipeline to online estimate ego‐motion and build a map of the
traversed environment, leveraging data from a 3D laser scanner, a camera, and an inertial …

We present Wildcat, a novel online 3D lidar-inertial SLAM system with exceptional versatility
and robustness. At its core, Wildcat combines a robust real-time lidar-inertial odometry …

In this paper, we present a novel visual-inertial navigation algorithm for low-cost and
computationally constrained vehicle in global positioning system denied environments by …

Map-centric SLAM utilizes elasticity as a means of loop closure. This approach reduces the
cost of loop closure while still providing large-scale fusion-based dense maps, when …

In this paper, we present a hybrid visual inertial navigation algorithm for an autonomous and
intelligent vehicle that combines the multi-state constraint Kalman filter (MSCKF) with the …

This paper shows how to carry out batch continuous-time trajectory estimation for bodies
translating and rotating in three-dimensional (3D) space, using a very efficient form of …

The ability to generate accurate and detailed three‐dimensional (3D) maps of a scene from
a mobile platform is an essential technology for a wide variety of applications from robotic …